Computer implemented method for quantifying the revelance of documents

ABSTRACT

A computer system comprising a processor, graphical output means and a computer readable storage medium storing instructions that when executed by the processor cause the processor to perform a method for quantifying and aggregating the relevance of documents.

RELATED APPLICATION

The present application is a continuation of application of U.S. patentapplication Ser. No. 16/504,132, filed Jul. 5, 2019 entitled “COMPUTERIMPLEMENTED METHOD FOR QUANTIFYING THE RELEVANCE OF DOCUMENTS”, which isa continuation of U.S. patent application Ser. No. 12/899,756, filedOct. 7, 2010 entitled “COMPUTER IMPLEMENTED METHOD FOR QUANTIFYING THERELEVANCE OF DOCUMENTS”, the disclosures of which are expresslyincorporated herein by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates to the field of data processing, and moreparticularly to a computer implemented method for quantifying anddensely displaying the relevance of documents. In particular, theinvention relates to the field of quantifying the relevance of patentdocuments.

BACKGROUND AND RELATED ART

The amount of information being generated and made publicly available inthe private, governmental and business sector has been tremendouslyincreasing over the last decades. Meanwhile, in most spheres ofbusiness, it is not any more possible to keep up-to-date by reading allthe documents available on a particular subject. This problem, alsoknown as the problem of “information overload”, has led to thedevelopment of several computer aided methods facilitating andaccelerating the retrieval, organization and evaluation of all theavailable and relevant data on a particular subject.

The optimal method for determining the relevance of documents for aparticular question depends heavily on the structure of the data objectscomprising the information of interest. A continuum of structurednessexists reaching from highly unstructured data structures such as BOnatural language text stored for example in the form of web pages tohighly organized data forms, e.g. entries in relational databases,wherein data is stored in tables according to a particular, structureddatabase schema.

Data being organized in highly structured data sources such as databasescan be interpreted and processed by computers e.g. by applyingappropriate retrieval requests such as SQL queries. However, it is atime consuming task for humans to develop a database schema suitable forthe data that shall be represented and stored by said database and toconstruct appropriate queries for each particular subject field a usermay be interested in. For this and other reasons, many documents whichmay be of relevance for a particular subject are never stored in astructured way and are stored as plain text instead, e.g. as html pageavailable via the world wide web. In addition, not all relevantinformation of data objects may be explicitly present in the databasebut may be information implicitly derivable from the connectivity ofdocument data objects relative to each other.

Plain text documents represent the other end of the continuum: naturallanguage text is, although semantically rich, highly unstructured. Itrequires sophisticated natural language processing methods to enable acomputer to extract meaningful information from plain text and toefficiently rank the relevance of text documents based on the plain textinformation. Due to these difficulties, methods trying to rank suchhighly unstructured documents often abstain from analyzing the documentssyntactically or semantically and rather rely on evaluating topologicalproperties of the network of documents. The topological informationconsists of links, e.g. citations. Such links are usually directed.Commonly, links are established by a document, the ‘source document’,citing one or multiple other documents, here referred to as ‘destinationdocuments’.

A data object representing a document may comprise additionalmeta-information. The meta-information comprises additional informationon the document and may include pointers connecting the document dataobject to other document data objects, the pointers thereby acting aslinks.

In the following, the term ‘linkage information’ will be used to denoteinformation on which document data object is linked to any otherdocument data object. Links may be stored separately from the linkeddata objects, may be contained in the plain-text section or themeta-information section of the source document data object, destinationdocument data object or both of them. A well known example for linkswithin plain-text sections of documents are hyperlinks, e.g. URLhyperlinks. A Hyperlink is a reference to a document or a text sectionthe user can directly follow, e.g. by clicking on an icon or a textphrase providing the hyperlink functionality (the hypertext).

The linkage information has been used to determine the relevance ofdocuments, in particular of documents having only littlemeta-information and lacking a common, semantically rich data structureallowing a more advanced way of quantifying the relevance of documentsrepresented by the data objects examined.

A method described in U.S. Pat. No. 7,058,628, also known as Google's‘page rank algorithm’, assigns importance ranks to nodes in a linkeddatabase, such as any database of documents containing citations or theWorld Wide Web. The rank assigned to a document is calculated from theranks of documents citing it. In addition, the rank of a document iscalculated from a constant representing the probability that a browserthrough the database will randomly jump to the document.

A further technique to retrieve, rank and display data objects isdescribed m U.S. Pat. No. 7,376,649. A global ranking value is hereinassigned to a data object based on a combination of the object'slink-based and text-based (e.g., word frequency) ranks. A ‘link-based’rank is derived from a vector-space cluster analysis, a ‘text-based’rank is derived from text features such as word frequency.

US2008243813 describes a method and system for calculating theimportance of documents based on transition probabilities from a sourcedocument to a target document.

One type of document being of particular relevance for many companiesand corporate consultants are intellectual property documents, e.g.patent documents, patent applications, utility patents and utilitypatent applications.

Various methods for evaluating the relevance of intellectual propertydocuments are known which have, however, severe methodologicalshortcomings and lead to wrong or incomplete results. For example,Trajtenberg, M., 1990, describes in “A penny for your quotes: patentcitations and the value of innovations” published in the RAND Journal ofEconomics 21(1), obstacles arising from the use of patents in economicresearch. The obstacles are caused by the fact that patents varyenormously in their importance or value. Hence, simple patent countscannot be informative about the innovative output of a company.Trajtenberg proposes to weight the patent counts by citations asindicators of the value of innovations, thereby overcoming thelimitations of simple counts.

Hall, B. H., A. Jaffe, et al., 2005, explores in “Market Value andPatent Citations” published by the Rand Journal of Economics 36(1):16-38 the usefulness of patent citations as a measure of the“importance” of a firm's patents. Hall comes to the conclusion that eachextra citation per patent boosts the market value of that patent by 3%.

Harhoff, D., F. M. Scherer, et al., 2003, describe in “Citations, familysize, opposition and the value of patent rights” published in ResearchPolicy 32(8), 1343-1363 that the number of citations a patent receivesis positively related to its value. References to the non-patentliterature are informative only in some particular technology fields.Patents which are upheld in opposition and annulment procedures andpatents representing large international patent families areparticularly valuable.

US 20070073748 describes a method for probabilistically quantifying adegree of relevance between two or more citationaily or contextuallyrelated data objects, such as patent documents, non-patent documents orweb pages. The relevance between two or more citationaily orcontextually related data objects is visualized by using iterativeself-organizing maps (“SOM”) generating a visual map of relevant patentswhich are to be explored, searched or analyzed.

U.S. Pat. No. 5,991,751 describes a data processing system maintainingfirst databases of patents and second databases of non-patentinformation of interest to a corporate entity. The system also maintainsone or more groups comprising any number of the patents from the firstdatabases. The system processes the patents in one of the groups inconjunction with non-patent information. Accordingly, the systemperforms patent-centric and group-oriented processing of data. A groupcan also include any number of non-patent documents. The groups may beproduct based, person based, corporate entity based, or user-defined.Other types of groups are also covered, such as temporary groups.

U.S. Pat. No. 6,556,992 provides a statistical patent rating method andsystem for independently assessing the relative breadth, defensibilityand commercial relevance of individual patent assets and otherintangible intellectual property assets. Said rating method providesmeans for patent valuation by experts, investment advisors, economistsand others to help guide future patent investment decisions. It isdescribed a statistically-based patent rating method and system wherebyrelative rankings are generated using a database of patent informationby identifying and comparing various characteristics of each individualpatent to a statistically determined distribution of the samecharacteristics within a given patent population.

SUMMARY OF THE INVENTION

The present invention relates to an improved, computer implementedmethod for quantifying and densely displaying the relevance ofdocuments, in particular patent documents.

The expression ‘densely displaying’ encompasses the display of aplurality of data values in a summarized form which can quickly becomprehended by a user. As often the case, users need to extractinformation contained in a set of documents without manually consideringthese documents one by one. For example, a user may be interested in theoverall relevance of a group of documents, e.g. a patent portfolio. Insuch cases densely displaying an aggregated relevance score of thedocuments can be preferable over e.g displaying a long ranked list ofdocuments. A user might also be interested in understanding thestrengths and weaknesses revealed in a document portfolio such as apatent portfolio. By densely displaying the aggregated relevance ofsubsets of an overall portfolio, areas of strength and weaknesses can bediscovered and quantified.

A significant, if not the largest proportion of the documents availabletoday are represented by data objects whose structuredness is locatedsomewhere in the middle of the continuum of structuredness: data objectsrepresenting said documents may contain a section of natural languagetext comprehensible only by a human or by a computer applying advancedNLP methods. However, said data objects in the middle of the continuumin addition comprise meta-information that can be used to group andevaluate a multitude of documents with the help of a computer. Further,those document data objects may comprise links in their plain-text ormeta-information section connecting them to other document data objects.

Embodiments of the present invention make use of structured, explicitinformation being available for each document data object as‘meta-information’ in combination with linkage information and externaldata to determine the relevance of a particular document family and thedocument data objects the document family comprises and to create a setof combined relevance score values which can be used to derive variousaggregate relevance scores values on a large set of document families.

In the following, various procedural steps are explained on aconceptional level with reference to ‘documents’ and ‘document families’to ease the understanding of the methodological principles. As a matterof course, the computer-implemented methods and procedures executingthose tasks do not handle abstract concepts but rather physical dataobjects interpretable and processable by a processing device. Documents,document families and groups thereof are represented on the physicallevel as data objects and data structures of various kinds, and thepresent invention is not limited to a particular programming language ora particular database system.

The meta-information of data objects comprises various properties of thedocument data object and may be represented e.g. in the form ofattributes of data objects or in the form of table columns in relationaldatabases of a particular database entry. The data contained in themeta-information of documents and their corresponding data objects canbe used for various classification tasks, e.g. for a classification bycountry, by technology field or by the document owner, e.g. a patentholder. A property of a document data object can, for example, comprisebibliographic information, such as the author, a publishing company, thetitle of the journal or book wherein a document is published, thepublication date, the language, the country wherein the document has aparticular status, or the legal status within said country. Legaldocuments such as patent documents may be valid in a limited set ofcountries only and their validity in each country may be limited to aparticular period of time. A property may likewise specify the date offiling or publishing a patent, a priority date, a country code, the nameof the company owning the patent, the inventor, and the like.

In the context of the present invention, the term ‘external data’ refersto data being indicative of a property of an object of the ‘externalworld’, said object of the ‘external world’ being different from thedocument whose relevance is to be determined. For example, the grossnational income is ‘external data’ as it is a feature of a country, nota feature of a particular document or document data object.

A ‘link’, as used in the context of the present invention, is any kindof computer-interpretable, directed connection between data objects,e.g. edges connecting one data object node to another data object nodein a directed graph wherein the nodes represent document data objects.

According to other embodiments of the invention, a link connectingdocument data objects may be implemented as a citation list stored e.g.as database table and connecting a citing document to one or multiplecited documents. In the following, a document data object containing aparticular link will be referred to as source document data object ofthe link. The document data object to which the link points to will bereferred to as destination document data object. Analogously, a documentcontaining a particular link will be referred to as source document ofthe link and the document to which the link points to will be referredto as destination document. A link may be stored in the plain-text ormeta-information of the source document data object, of the destinationdocument data object, or both document data objects, or in a separatedata object or data storage.

According to further embodiments of the invention, undirectedconnections between data objects are represented by two oppositedirectional connections and thus be each considered as two links.

The term ‘documents’ refers to electronic documents of various kind, forexample, scientific, technical, business and/or legal documents, inparticular patents, patent applications and technical or scientificpublications. The documents are represented in the form of ‘dataobjects’. Accordingly, ‘meta information’ of documents, ‘documentproperties’ and the like are represented e.g. as constants or variablesof the data object representing the electronic document. The expression‘document families’ also encompasses one or more data objectsrepresenting a family of documents sharing a particular property valueor property value range.

The expression ‘document data objects’, or simply ‘data objects’encompasses in the following any kind of data object which represents anelectronic document. The document data objects can be implemented e.g.as data object instances of a particular class in a piece of softwarewritten, for example, in an object oriented language. A document dataobject may also be implemented as an XML document or an entry of adatabase or a similar data structure. A data object can be manipulatedby means of a programming and/or database query language and comprisese.g. bibliographic data or other meta-information of the document, thetext of the document and may also comprise information on otherdocuments linking to said document or being linked by said document.

The term ‘data aggregation’ as used herein is any process in whichinformation is gathered and expressed in a summary form. Dataaggregation allows the gathering of information about particular dataobjects having been grouped together based on specific properties.

An ‘aggregated view’ is a view provided to a user, e.g. via a graphicaluser interface such as a computer screen or a print-out, on data havingbeen aggregated for a particular group of data objects. An aggregatedview presents some or all data contained in the aggregated data objectsin a condensed summary form, thereby providing the user with anintuitive and quickly comprehensible presentation of all or some of thedata contained in a multitude of aggregated data objects. Providing anaggregated view can comprise, for example, displaying the number of dataobjects aggregated, displaying an aggregated relevance score, ordisplaying any other form of aggregated data value, e.g. an aggregateddata value having been derived by aggregating a particular propertyvalue of all aggregated data objects. The aggregated data value may bedisplayed as alphanumerical character, may be encoded by a color schemaand/or may be encoded by using a set of predefined images or graphicalobjects such as squares, circles or the like. An aggregated viewcomprising one or more aggregated score values is, for example, a screenimage of an electronic display or a printout displaying said aggregatedscore value. An aggregated view being derived from one or moreaggregated score value is, for example, a screen image or printout,wherein the shape, color, and/or (in the case of the electronic display)dynamic behavior of the displayed graphical elements depends on theaggregated score value.

The term ‘computer readable storage medium’ as used herein encompassesany storage medium which may store instructions which are executable bya processor of a computing device. In some embodiments, a computerreadable storage medium may also be able to store data which is able tobe accessed by the processor of the computing device. An example of acomputer readable storage medium include, but are not limited to: afloppy disk, a magnetic hard disk drive, a solid state hard disk, flashmemory, a USB thumb drive, Random Access Memory (RAM) memory, Read OnlyMemory (ROM) memory, an optical disk, a magneto-optical disk, and theregister file of the processor. Examples of optical disks includeCompact Disks (CD) and Digital Versatile Disks (DVD), for exampleCD-ROM, CD-RW, CD-R, DVD-ROM, DVD-RW, or DVD-R disks. The term computerreadable-storage medium also refers to various types of recording mediacapable of being accessed by the computer device via a network orcommunication link. For example data may be retrieved over a modem, overthe internet, or over a local area network.

The term ‘computer memory’ or ‘memory’ as used herein encompasses acomputer readable storage medium which is directly accessible to aprocessor. Examples of computer memory include, but are not limited to:RAM memory, registers, and register files of a processor.

The term ‘computer storage’ as used herein encompasses any non-volatilecomputer readable storage medium. Examples of computer storage include,but are not limited to: a hard disk drive, a USB thumb drive, a floppydrive, a smart card, a DVD, a CD-ROM, and a solid state hard drive. Insome embodiments computer storage may also be computer memory or viceversa.

The term ‘computer system’ as used herein encompasses any devicecomprising a processor. The term ‘processor’ as used herein encompassesany electronic component which is able to execute a program or machineexecutable instructions. References to the computing device comprising“a processor” should be interpreted as possibly containing more than oneprocessor. The term ‘computer system’ should also be interpreted topossibly refer to a collection or network of computing devices eachcomprising a processor. Many programs have their instructions performedby multiple processors that may be within the same computing device orwhich may be even distributed across multiple computing device. The term‘computer system’ may be interpreted herein as being a ‘computingdevice.’

The objective of embodiments of the present invention is to provide animproved computer-based method for the quantification and the aggregateddisplay of the relevance of documents for a particular purpose orcriterion.

In a further aspect, it is the objective of embodiments of the presentinvention to provide an improved method for the quantification of therelevance of documents for which meta-information and information on itsconnectedness to other documents via links is available. As the‘relevance’ of each piece of information may depend on the user and theparticular goal of executing the relevance calculation, m a furtheraspect it is the objective of embodiments of the invention to providemeans to flexibly evaluate the relevance of a large set of documents,wherein the categorization of documents is executed based on a multitudeof different criteria specifiable by the user.

In a further aspect, the information gathered from a multitude ofdocuments is displayed in a dense and intuitively comprehensible way.The problem of information-overload shall be resolved for any kind ofdocument, in particular patent documents, by pointing the user to themost relevant documents and by providing a method to densely display theresults to a user in the form of an ‘aggregated view’.

Electronic displays and paper-based printouts are of limited size.Providing the results of an aggregating function, e.g. an aggregatingscore in the form of an aggregated view is highly advantageous as itallows to provide a user with in-depth, comprehensive data that canquickly be comprehended.

By ranking documents and calculating an aggregate relevance score frommeta-information and linkage information derived from multiple documentsallows a user (whose time and information processing capacity is alwayslimited) to quickly comprehend the essence of the information containedin a collection of documents also when the size of the collection isvery large (e.g. more than 1.000.000 documents).

In one aspect, the invention provides a computer implemented method forquantifying and aggregating the relevance of documents, the documentsbeing represented by document data objects, the method comprising:

-   -   assigning documents to one or multiple document families, each        document family comprising one or multiple documents;    -   calculating, for each document family, a document family        coverage score DFCS, the document family coverage score being        indicative of the validity of the document family in a category,        whereby the validity is calculated from one or more properties        of each document belonging to said document family;    -   calculating, for each document family, a document family linkage        score DFLS, said document family linkage score being calculated        by        -   finding one or more document links, each document link            connecting a source document to a destination document, each            destination document belonging to said document family, each            source document belonging to another document family,        -   finding one or more document family links, whereby each            document family link connects a source document family with            said document family, said document family acting as            destination document family, wherein the existence of each            document family link is derived from the one or more found            document links and wherein the DFLS is derived from the            existence and weight of the one or more found document            family links;    -   calculating, for each document family, a document family        combined relevance score DFCR by multiplying the document family        coverage score DFCS and the document family linkage score DFLS        having been calculated for each document family;    -   grouping document families into one or more portfolios, each        portfolio comprising one or more document families;    -   displaying, for each document portfolio, an aggregated view, the        aggregated view comprising or being derived from one or more        aggregated score values, the one or more aggregated score values        being calculated by applying an aggregating function on the        DFCR, the DFLS, or the DFCS value of the one or more document        families of said portfolio.

One example for a document type for which an aggregated view can beprovided are patent documents. Often, significant differences betweenthe patent portfolios of competing companies exist, as companies mayfollow different strategies in filing patens (maximizing the totalnumber of patens or maximizing cost efficiency by filing only the mostpromising inventions), and as companies may not all be involved in R&Dto the same extent or may employ R&D teams of different inventive skill.Existing patent ranking methods are hampered by the fact that neitherthe linkage information alone nor the information explicitly stated inthe data objects provides sufficient information to rank patentdocuments according to their true relevance to the user.

In still a further aspect, it is an objective of embodiments of thepresent invention to provide an improved method for reliablybenchmarking patent portfolios.

Providing an improved patent benchmarking approach is only one of amultitude of embodiments of the present invention. Other embodiments ofthe invention exist for other document categories, e.g. technicaldocumentations, newspaper articles, medical records and the like. Tosimplify matters, and without limiting the spirit and scope of theinvention to patent documents, the general principles of the inventionare elucidated in the following by embodiments having been speciallyadapted for the purposes of patent portfolio benchmarking. Those skilledin the art will know how to apply the teachings revealed in thisdocument to rank sets of documents of other types which are alsorepresented by interlinked document data objects comprisingmeta-information.

The objectives mentioned above are solved by the features of theindependent claims. Preferred embodiments of the invention are given inthe dependent claims.

According to preferred embodiments of the invention, the accuracy ofdetermining the relevance of documents is improved by taking intoconsideration the meta-information of the document data objects as wellas linkage-based information. The improvement is particularlysignificant for documents having been published recently. Recentlypublished documents have usually been cited only scarcely and have,accordingly, only a small ‘linkage score’ or ‘link-based relevancescore’, as a linkage score in general correlates with the number ofother documents citing a particular document. By taking intoconsideration meta-information in addition to a link-based relevancescore, the accuracy of calculating a relevance score is improved.

According to further embodiments of the invention, meta-information ofthe document, linkage information of the document and external data isused as input for calculating an aggregated relevance score value.

Patents are legal rights granted by governments in order to bothstimulate inventions and their disclosure to the public. A patent is alegal device that grants an inventor market exclusivity over a newinvention. As patents are granted by national law, they are only validwithin the respective country. In ail countries wherein the patent isnot valid, the invention can be freely imitated by competitors. Usually,the patent application is filed only in a very limited set of countriesin order to reduce costs. Further, the application may have beenrejected by the patent offices of some of the countries. For saidreasons, the legal protection of an invention is usually effective inonly a fraction of world markets.

In the following, the term ‘patent’ and ‘patent document’ should beconsidered as referring to any kind of intellectual property rightdocument, including patent document, patent applications, utilitypatents and utility patent applications.

Some users will perceive the relevance of a patent in their applicationcontext to be intimately related to the patent's economic value. Due tothe extreme variance of economic value of different patents (the 20%most valuable patents represent 90% of total patent value), an estimateof the economic relevance of a patent portfolio simply by counting thenumber of patents does not suffice even for portfolios of large size. Inseveral studies it has been shown that the number of citations receivedby a patent could be used as indicator of the economic relevance.However, there is usually a time delay of several years between thepublication of a patent application and its first citation establishinga link between the citing source document and the cited destinationdocument. Many patents may not be cited at all during their wholevalidity period. Solely ‘link-based’ or ‘citation-based’ methods fordetermining the relevance of a set of patent documents therefore willproduce unrealistically low scores for recently published patentdocuments. As a result, a purely link-based approach may be biased infavor of older patent documents which may not necessarily be morerelevant. This problem is an obstacle to any citation based relevanceestimation and not limited to the relevance ranking of patent documents:whenever a score is derived based on the number of other documentslinking to a particular document and wherein in addition the number oflinks depends on the age of the linked document (as the case with anycitation based links), there exists a bias in favor of older documents.

According to further preferred embodiments of the invention, theaccuracy of determining the relevance of documents is further improvedby taking into consideration external data. A combined relevance scoreis calculated based on the link-based, the document data-object basedand external data based information. Depending on the embodiment of theinvention, the document data object based information comprisesmeta-information of the document data objects and/or information beingcontained in the document text and or information being derived byprocessing the meta-information and/or document text information. Thisapproach is particularly advantageous, as it allows, for example, tonormalize the relevance score according to one or multiple referenceparameters which may vary in the course of time.

If, for example, the economic impact of a set of patents belonging toone patent family is to be calculated, one possibility to do this wouldbe to count the number of patens being valid in different countries. Thelarger the number of countries wherein a patent of the family is valid,the higher the economic relevance of said patent family. According to afurther embodiment of the invention, the accuracy of the calculatedscore is improved by considering, for each country, its significance forthe given aggregation task. The significance can be measured, forexample, based on the gross domestic income GDI or a similar figurebeing representative of the economic power of a country. The annual GDIfigures used for the country specific weighting may change over time.Deriving the data from an external source, e g. the World Bank, on aregular basis does not only improve the accuracy of the relevance scorebut in addition provides means to adapt the relevance score calculationto changes in the external settings being relevant for the scorecalculation.

Depending on the implementation, the external data used to calculate thescore may be stored as part of the meta-information. Still, in thecontext of the present invention, such data will be referred to as‘external’ as it comprises data being indicative of a property of anobject of the external world, and not of a document data object it maybe stored in, for example the GDI of a particular country. Typically,but not necessarily so, said external data is derived on a regular basisfrom external data sources, e g. governments or national orinternational organizations like banks, insurance companies or healthorganizations.

According to a further embodiment of the invention, the external datamay be supplemented or replaced by company-private data. Company-privatedata may be useful for a company to further adapt the portfoliorelevance analysis to its particular needs, thereby increasing theaccuracy of the aggregated score calculation. For example, the GDI is ingeneral considered as good indicator of the economic power of a country.In case a company executing a portfolio analysis is in possession ofother indicators being of higher relevance for the purposes of thecompany, the company may use this indicator instead of the GDI. Forexample, if the company develops and sells pharmaceutical products andis in the possession of turnover figures for pharmaceutical products inall economically relevant countries of the world, the accuracy of theportfolio analysis may be further improved in respect to the needs ofthe company by using the pharmaceutical turnover figures instead of theGDI. The feature of allowing a user to specify the kind and content ofexternal data used for normalizing the relevance scores provides thebenefit that the significance of each particular country, e.g. from theeconomic angle, which may vary greatly depending on each respectivebusiness sector or technology field, can be far better estimated basedon company or business sector specific weights than on highly generalindicators of economic relevance such as the GDI.

By combining selected properties of the document data object, e.g. thecountry a patent document is valid in, with external data, such as theGDI of that country, it is possible to improve the accuracy of thecalculated relevance score.

Documents are grouped into document families before the document familylinkage score and the document family coverage score is calculatedwhenever applicable.

According to a preferred embodiment of the invention, a method forquantifying and aggregating the relevance of documents is provided whichis based on the specification of one or more document families and thecalculation of three relevance score values:

The ‘document family linkage score’ DFLS in the context of the presentinvention is a relevance score value having been calculated for aparticular document family, the relevance score value being indicativeof the frequency and quality of links, e.g. citations, pointing todocuments of said particular document family.

The ‘document family coverage score’ DFCS in the context of the presentinvention is a relevance score value having been calculated for aparticular document family, said relevance score value being indicativeof the coverage of the document family in respect to a particularcategory. The coverage of a document family of a particular category canbe determined, according to embodiments of the invention, by determiningthe value of a property assigned to each document of a document familyand by calculating a DFCS score for a document family in dependence ofthe property values of each document in said document family. Forexample, a category for which the coverage of a document family shall bedetermined, can be a geographic region, e.g. one or more continents, aneconomic zone or a particular selection of countries. Depending on theembodiment, the property can be indicative of political, economic orgeographic properties having been assigned to a document of the documentfamily.

According to some embodiments, said property is indicative of thestatus, e.g. the legal status, of a document in a particular country.According to some embodiments, the determined document family coveragevalue is weighted based on the impact of each entity represented by saidproperty for the respective document aggregation task. For example, incase the properties used for calculating the DFCS score of a documentfamily are country-specific weights, a country-specific feature beingindicative of the impact of said country for the aggregation task couldbe the GDI of the country being indicative of its economic strength.

The ‘document family combined relevance score’ DFCR in the context ofthe present invention is a relevance score value being calculated for aparticular document family as the product of the DFCS and the DFLSvalues of said document family.

According to embodiments of the invention, any of said three scorevalues calculated for a document family and can be assigned to eachdocument contained in the document family for which the scores weredetermined. Said assigned relevance score value is used as the‘relevance score’ or ‘rank’ of a document. This rank may be used toretrieve and display documents ordered according to their rank, the rankbeing indicative of the relevance of a particular document for aparticular question.

According to further embodiments, a ranked list of document families maybe provided and displayed in addition to or instead of a ranked list ofdocuments. Given a display of a limited size, the display of the highestranking documents or document families on the screen assists a user inreading and evaluating only the most relevant documents.

According to some embodiments, the documents are patent documents andthe document families are patent families representing an invention. Theset of documents whose relevance is to be determined is a set of patentsheld by a company. In case the user wants to retrieve the most relevantpatents of the company, he may apply the method in order to retrieve alist of patens ranked e.g. by the patent family combined relevance scoreDFCR of the patent family the patent documents belong to. The list showsthe most relevant patents on the top. Alternatively, the user may chooseother subsets, e.g. a set of patent documents belonging to a particulartechnology field, a set of patent documents having been filed by aparticular department of the company or being valid within a selectedperiod of time or a selected set of countries.

Alternatively or in addition to calculating the DFLS, the DFCS or theDFCR scores of all document families of a particular set of documents,e.g. a document portfolio, derivative score values may be calculated.

A ‘portfolio’ encompasses a set of document families whose documentsshare at least one common property, e.g. the technology field, thecompany owning/holding a document, a period of time or a particularcountry within which a document is valid. In case the documents arepatent documents and the portfolio is created by grouping all patentsheld by the same company into one portfolio, the application of themethod results in an improved method for evaluating the competitivestrength of a patent portfolio of a particular company.

A derivative data value is a data value having been obtained by applyinga mathematic function on another data value. According to furtherembodiments, derivative relevance score values are calculated which are:The portfolio size PSI=Number of document families of a portfolio havinga DFCS value larger than 0.

The portfolio strength PST=Sum of the total DFCR score values of alldocuments in the portfolio.

The field share FSH=Ratio of the sum of the DFCR score values of alldocument families of a portfolio to the sum of the DFCR score values ofa superset of document families, whereby all document familiesconsidered in said calculation belong to a particular field for whichthe FSH value is calculated. The superset of document families can be,for example, the totality of document families examined. The FSH mayfurther be refined by considering only document families being valid ata particular sheet date or meeting any other condition.

FSH=Σ(DFCR_(i1u), . . . , DFCR_(inu))/Σ(DFCR_(jfu), . . . , DFCR_(jnu)),wherein the portfolio i may, for example, represent all documents of aparticular person or company, u may represent the field considered and jmay represent a larger set of documents, for example all documentsexamined. A ‘field’ as used herein can be any property assigned to adocument family, for example, a technology field, an inventor or author,or the like. Each document family may have assigned multiple data valuesper field. For example, the field ‘technology field’ of a documentfamily can have assigned multiple different technology fields, forexample if the document relates to different technological fields suchas ‘genetics’ and ‘microbiology’. At least some types of fields of adocument family are also assigned to the documents of said family.According to some embodiments, all documents of a document family areassigned the technology field assigned to the document family.

The portfolio linkage score PLS=Average DFLS of all document families ofa portfolio having an DFCS value larger than 0.

The portfolio coverage score PCS=Average DFCS of all document familiesof a portfolio having an DFCS value larger than 0.

Said score values have been observed to be particularly suited foraccurately representing various aspects of the relevance of a documentfamily.

According to a further embodiment, by executing a drill-down analysis,the FSH value or any other aggregate document family score may bedetermined for a subset of document families belonging to a particularperson or company, belonging to a particular technology field and/orbeing valid at a particular sheet date, or any other sub-sets ofdocument families. A drill-down analysis is a specific analyticaltechnique whereby the user navigates among levels of data ranging fromthe most summarized (up) to the most detailed (down). During adrill-down analysis, a currently evaluated sub-set of document family isconsidered as current portfolio for which said derivative relevancescores, e.g. PSI, PST or FSH can be calculated.

Instead or in addition to displaying a list of ranked document families,the aggregated score value may be displayed graphically, e.g. on thescreen of a computing device such as a computer or a mobile phone, or asprintout. The information may be displayed on the same machine where thedocument relevance scores were calculated or presented on a remotescreen via a network, e.g. by presenting the results on an HTML pageaccessible via the Internet by a browser of a client machine.

According to a further embodiment, the total set of documents ispre-processed in a filtering step to filter out all those documentswhich do not meet various quality criteria, e.g. in regard tocompleteness, consistency or the type of the document and itsproperties. Thus, only documents meeting some quality requirements willbe used for calculating the relevance scores DFLS, DFCS and DFCR.

According to a further embodiment, the documents are patent documentsand derived by parsing XML files obtained from the DOCDB and INPADOC-PRSof the EPO. The INPADOC-PRS database is part of the European PatentOffice's European Patent Information and Documentation SystemsDirectorate and comprises legal status information of multipleauthorities. The legal status codes issued by various patent offices aremapped to universal legal codes stored in additional, internal databases.

In the following, the steps for providing a user with an aggregated viewaccording to various embodiments of the invention will be explained ingreater detail.

1. Assigning Documents to One or Multiple Document Families, EachDocument Family Comprising One or Multiple Documents.

According to embodiments, the documents can be dynamically queried fromone or more document sources, e.g. data bases, files, the internet orthe like. For many document types, in particular patent documents, agrouping of closely related documents into document families isadvantageous for several reasons. At first, calculation time may bereduced as the number of document families typically is smaller than thenumber of documents. Further, this step reduces the variance between theexamined data objects (document families are compared, not singledocuments) as the data basis for each document family becomes larger.Depending on the type of document processed, there may be additionalbeneficial aspects. In the case of patents, for example, documents arepreferentially grouped into patent families. A grouping of documentsinto patent families is advantageous as all documents of a patent familymay represent the same invention. Taking a whole patent family insteadof a single patent document as the basis for calculating relevancescores helps to reduce systematic biases, e.g. towards patents from oneauthority, and the influence of singular events and outliers;

The grouping of documents into document families depends on the type ofdocument to be processed and on the kind of information considered as‘relevant’ by the respective user. In case the documents are technicaldocuments, technical documents of different versions may be groupedtogether if they relate to the same device. In case the documents arelegal documents, documents may be grouped into the same document familyif they share the same case number.

In case the documents are web pages, books, articles or texts and theuser is interested in the extent of the potential audience thendocuments may for example be grouped into one document family if theycontain the same content but are written in different languages.Similarly, if the user is interested in the extent or diversity ofdiscussion or knowledge on a particular topic, then documents may begrouped into one document family if they share the same topic.

According to some embodiments, clustering or classification algorithmsare used to group documents into document families. A multitude of othergrouping options exist. A person skilled in the art knows how thegrouping of documents into families may be adequate in each particularuse case scenario.

2. Calculating, for each document family DF_(Dest.) a document familycoverage score DFCS_(DFDest).

The DFCS is indicative of the coverage of the document family in aparticular category.

According to embodiments, the coverage of a document family iscalculated from at least one property of its documents.

According to embodiments of the invention, the calculated DFCS isindicative of the coverage of the document family in any user-selectedcategory. For example, if the user is interested in the extent of thepotential audience of the document family, the coverage can becalculated based on the document property ‘language’. In this case, thecalculated DFCS will be indicative to what extent a certain documentfamily comprises documents in different languages.

According to further embodiments, in case a user is interested in theextent or diversity of discussion on a particular topic, the DFCS scoreis calculated for a document family based, for example, on theproperties ‘document length’, ‘publisher’, ‘author’, ‘geographic origin’or the like of each document contained in said document family. A personskilled in the art knows how the document property or documentproperties of the documents of a document family may be adequatelychosen in a particular use scenario for calculating the coverage of auser-selected category by a document family.

According to some embodiments, the impact of a document in respect to aparticular category is expressed by means of a weighted score w_(c).According to some embodiments, said weighted score is indicative of thevalidity of a document in a particular country.

According to other embodiments, said weighted score w_(c) is indicativeof the size of the potential audience being able to or being expected toread a language of a particular document. For example, if a user isinterested in the extent of the potential audience of document familiesthe language coverage of the document family can be calculated from theindividual documents by assigning each document a property in the formof a weighted score w_(c) indicating the size of the potential audiencebeing able to or being expected to read that language. Likewise, thepublishing coverage of a document family can be calculated for examplebased on the document property ‘publisher’ of documents in the documentfamily, whereby said property is weighted by the reach of each publisherin terms of readers. A person skilled in the art will know how theweights may be adequately chosen in a particular use scenario.

In some embodiments the DFCS is indicative of the geographic coverage,e.g. the validity of a document family in a geographic territory withinwhich said documents of the document family are valid. The validity isderived from at least one property of the document. The validity of thedocument family is calculated from the validity of the documentsbelonging to said document family and having assigned as property anidentifier of a particular country. The geographic territory is, forexample, a geographic region comprising multiple countries.

According to preferred embodiments, each documents has assigned multipledifferent properties, thereby allowing the calculation of a DFCS scorevalue for different categories of interest.

In the following, an embodiment calculating the validity of a documentfamily for a geographic territory (territory) will be described ingreater detail which is based on the validity of each document in aparticular country.

For example, if the documents are patent documents, their validity, i.e.their legal status in a particular country or probability of obtaining aparticular legal status in said country, are used to calculate thevalidity of the patent family in a set of countries, e.g. a continent.According to said embodiments, each document is assigned a countryidentifier as property, said country being, for example, the country inwhich said document was published or filed as patent application. Adocument is valid in said assigned country at a particular sheet date,if the sheet date is later than the filing date of the patent and thepatent has not yet expired or has been invalidated for other reasons. Incase the patent cites another patent as priority patent, the filing dateof the priority document may be taken instead of the filing date of saidpatent.

According to embodiments of the invention, the validity of a patent in acountry c is expressed by means of a weighted score w_(c). The weightedscore w_(c) is a weight being indicative of the probability that apatent is or will be granted for a patent document.

According to some embodiments, the score w_(c) indicates, whetherdocument DOC belonging to document family b is valid, invalid or pendingat the sheet date in country c. In case a document DOC belonging todocument family b is valid in country c at sheet date, then the documentfamily b is valid in country c at sheet date. A patent document haspending legal status in a country if the date of filing the document is<=sheet date, and if sheet date is <date of expiration of the patentdocument, and if the granting date >sheet_date or no granting date wasassigned at all.

Depending on the status of a patent document in a particular country,different score values may be assigned to the document.

According to one embodiment, the score w_(c) is

-   -   1, if first day of validity of document DOC in country c<=sheet        date <date of expiration of document DOC,    -   0.7, if the filing date of document DOC in country c<=sheet date        <date of expiration of document DOC, and if in addition DOC was        not assigned a granting date yet,    -   0, if sheet date>=expiration date of document DOC or sheet date        <first day of validity of document DOC. The first day of        validity can be, for example, the day of priority of the patent        document.

Said scores are indicative of the probability of obtaining legalprotection for a patent document. Said score may be 1 for granted andcurrently valid patents and 0 for invalid patent documents.

In case the document is a patent document, the first day of validity isthe date of priority of the patent based on DOC and the date ofexpiration of document DOC is the day at which a patent becomes invalidin a country because it has expired, was annulled or lost legalprotection for any other reason.

If document family DF1 comprises the documents DOC1, DOC2 and DOC3,wherein DOC 1 was valid in France at sheet date while DOC2 was valid inthe USA at sheet date and DOC3 was filed in Germany and was invalid atsheet date, then the patent family DF1 was valid in France and the USAat sheet date.

Said embodiment is particularly advantageous for documents representingpatent applications. If a patent has expired or has become invalid forother reasons, the weighted score w_(c) is 0. In case it is valid, thescore is 1. In case the patent application has been filed in aparticular country, the average probability of obtaining protection bylaw, which is currently about 70%, is used as weighted score as long asthe decision if a patent right will be granted is pending.

According to further embodiments of the invention, other probabilityvalues, e.g. country specific, company specific or technology fieldspecific probability values of obtaining a valid patent can be usedinstead of ‘0.7’ and ‘1’.

According to a preferred embodiment, EP patent applications are treatedas patent applications having been filed in all EP states until they areeither granted a patent or finally rejected. WO-applications are treatedwithin a certain period, e g. the first 40 month, after filing as patentapplications filed in all PCT states. If a country is covered by anational as well as an EP and/or a PCT patent application, the countryis considered only once while calculating the PFCS.

According to a preferred embodiment of the invention, the significanceof a property, e.g. the economic power of a country, is considered inaddition and a score wp_(c) being dependent on said significance iscalculated. According some embodiments, the wp_(c) value is calculatedfor a particular document DOC and a particular country c by weightingthe w_(c) value in dependence on the impact of country for theparticular aggregation task, e.g. in dependence on the economic power ofa country:

${wp}_{c} = \frac{{w_{c}}^{*}{GNI}_{c}}{{GNI}_{REF}}$

-   -   wherein GNI_(C) is a parameter being indicative of the impact of        a country c. GNI_(c) can be, according to embodiments of the        invention, the gross national income of a country c.    -   wherein GNI_(REF) is a parameter being indicative of the        significance of a reference country, e.g. the gross national        income of the USA,    -   wherein w_(c) is a weight being indicative of the legal status        of document DOC belonging to document family b in country c at        sheet date.

According to embodiments of the invention, the document family coveragescore DFCS is calculated for each document family b as the sum of thewp_(c) values assigned to all documents DOC of the document family b andfor all countries considered. The term ‘all countries considered’encompasses, according to some embodiments, all countries having beenassigned to any of the documents DOC. According to further embodiments,a sub-selection of countries is considered for calculating the DFCSvalue of the document families. According to embodiments, the DFCS valueof a document family b is calculated as:

DFCS _(b)=Σ(wp _(c))

In terms of a less condensed formula:

DFCS _(b)=Σ([w _(c) *GNI _(c)]/GNI _(REF))

wherein Σ indicates the sum over all documents of document family b andfor all considered countries c.

According to some embodiments, the w_(c) value used for calculating acountry-impact-specific wp_(c) value is calculated as describedpreviously, i.e. based on a weighting of each document according to itslegal status in a particular country. Said embodiments are particularlyadvantageous for patent documents.

According to other embodiments, the w_(c) value used for weighting andcalculating a w_(pc) value and a final DFCS value is a constant beingequal for all documents of a document family, a data value being derivedfrom a property of the document, or a data value being indicative of thesignificance of the document, e.g. in respect to a particular technologyfield.

According to some embodiments, each value being indicative of thesignificance of a country can be replaced by a user-specific value.According to some of said or other embodiments, a reference parameterGNI_(REF) can be selected or specified by the user via the graphicaluser interface. For example, a user may load a set of sales figuresachieved by his company in each country c into the computer system, e.g.by reading a plaintext file comprising the sales figures. Saidcountry-specific sales figures are then used instead of the grossnational income GNI for determining the country-specific significance ofa document. The user may select another country as reference countryinstead of the USA, e.g. via a checkbox list or a drop-down list. He mayalso manually specify the reference value, e.g. specify a particularimaginary annual sales figure considered as reasonable reference value.

3. Calculating, for Each Document Family b, a Document Family LinkageScore DFLS.

The DFLS of a particular document family is derived from one or moredocument links, each document link pointing from a source document of asource document family to a destination document of said documentfamily. Said particular document family acts as destination documentfamily.

In case two document families A and B each comprise one or moredocuments acting as source documents and pointing to a destinationdocument of the respective other document family, the two documentfamilies A and B are connected to each other via two document familylinks, one pointing from A to B, and one pointing from B to A.

According to further embodiments of the invention, the document linksare predefined or defined dynamically, each document link being selectedfrom the group comprising:

-   -   hyperlinks,    -   pointers connecting data objects,    -   adjacency matrices,    -   document citations and document references mentioned within the        text of a document, and    -   document citations and document references contained in the        meta-information of a document.

A pointer as used herein is a memory address connecting a first and asecond data object. An adjacency matrix is a matrix of documentidentifiers specifying which document cites or links to anotherdocument. Any kind of electronic representation of a citation orreference mentioned within a document text or the meta-information of adocument and pointing to another document can be considered, accordingto embodiments of the invention, as document link.

Depending on the embodiment of the invention, a document link may beexplicitly specified and stored in a data storage area within or outsidean electronic document or it may be dynamically calculated anddetermined during the execution of a method based on variousstatistical, natural language processing-based, or machine learningbased techniques which are able to detect a relation between twodocuments. Such a relation may be, for example, a dynamically calculatedsimilarity score, a co-citation relation, or the like.

According to embodiments of the invention, the document links used toderive the document family linkage scores are weighted. According tosome embodiments, the weight a of a document link is derived based onthe ‘linkage quality’ or ‘citation quality’ in case a link was specifiedin the form of a citation.

According to some embodiments, the document linkage weight is derivedfrom a data value being indicative of the quality of the citations orlinks issued by an instance such as, e.g. a patent office or aparticular patent examiner citing prior art documents as the result of asearch. It is assumed that the higher the average number of linksintroduced per source document by the link issuing instance, the lowerthe relevance of each single link or citation. Accordingly, the documentlinkage weight value is inversely proportional to the average number ofcited documents of said patent office.

According to further embodiments of the invention, each document link isweighted according to the field the source document belongs to, e.g. thetechnology field. Links, e.g. citations, are considered less relevantfor fields wherein it is common to cite a multitude of not necessarilyclosely related documents.

According to further embodiments, a citing authority specific qualityvalue is used as document linkage score value, said citing authorityspecific quality value being indicative of the authority having cited aparticular document. Said authority can be, for example, an inventor, anexaminer or a 3^(rd) party;

According to further embodiments, a document linkage score value iscalculated based on a citation category of the destination document. Adestination patent document is a patent document being cited. Suchcitation categories are, for example, the ‘A’, ‘Y’ and ‘X’ classes usedby the International patent office to classify the documents retrievedin a search, whereby ‘A’ indicates low relevance, ‘Y’ as only partialrelevance and ‘X’ a high relevance.

According to further embodiments, a quality value being derived from afurther property of the source document is used to calculate thedocument linkage weight α. Said property-derived quality value isindicative of the relevance of said document for a user. For example, ifthe citation quality was determined to be particularly high in adetermined time frame, said time frame information may be used asdocument linkage quality weight. According to other embodiments, afurther property value of the destination document is used to calculatesaid document linkage weight. For example, said property can be the sizeof an organisation, the validity of a document in a particular marketplace or the identity of the document owner, e.g. of a competitor.

According to further embodiments, the field of the source document isused to determine the document link quality value. Said quality value isinversely proportional to the average number of documents cited by adocument having assigned said field.

According to further embodiments, the field of the source document andthe field of the destination document are used to determine the documentlink quality value. Said quality value is proportional to a predefinedor dynamically calculated similarity score, the similarity score beingindicative of the similarity of the source document and the destinationdocument. For example, if the cited document DOC1 belongs to thetechnology field ‘genetic engineering’, a first citing document DOC2belongs to the technology field ‘mouse genetics’ and a second citingdocument DOC belongs to the technology field ‘Telecommunications’, thanthe quality value for the document link DOC2→DOC1 will, depending on theembodiment, be higher or lower than DOC3→DOC1 as the technology field ofDOC1 is closer to that of DOC2 than to DOC3.

According to further embodiments, the weights of the document links aredirectly derived in dependence on a particular technology field. Atfirst, each document link is assigned to one or more technology fields.Depending on the embodiment, this assignment can comprise: assigning thetechnology field of the source document to the document link; assigningthe technology field of the destination documents to the document link;assigning the technology field shared by the source document and thedestination documents to the document link. In a second step, eachdocument link is assigned the technology specific weight, said weightbeing indicative of the relevance of the respective technology field forthe user.

In the following, an embodiment of the invention calculating thedocument linkage score based on the citation quality of patent officesshall be described.

At first, citation statistics for all relevant national andinternational patent offices are determined.

Each citation statistic comprises information on the average number ofcited prior art documents for each patent document examined by aparticular patent office o and being published in a particular period oftime, e.g. a calendar year y. Each link connecting a source document d1with the cited prior art document d2, d2 acting as destination document,is considered as ‘document link’. According to some embodiments of theinvention, cited documents not being patent documents, e.g. scientificpublications or textbooks, are ignored.

If, for example, patent office o1 published 4000 patent documents in2004, said documents comprising 12000 citations of prior art documents,the average citation per published patent document of office o1 is 3.Another office may have published 6000 patent documents in the same yearwhich in total comprise 24000 citations of prior art documents. Theaverage citation per published patent document is 4 for office o2. Asoffice o2 cites more prior art documents per patent document than officeo1, it is assumed that each single citation issued by office 1 isfocused on a more specific and more relevant set of documents.Accordingly, the document link quality value of links being based oncitations of office o1 is higher than for office o2.

Other embodiments of the invention use related approaches to assignweights to document links. A person skilled in the art will choose amethod of assigning weights to documents appropriate to the type ofdocuments to be ranked and to the type of instance assigning the linksbetween the documents.

After having determined the citation statistics for the patent offices,all document links are weighted according to the calculated patentoffice statistics. For example, for a particular documentcitation/document link dl1 issued by patent office o1 in 2004, adocument linkage weight α_(o1) is calculated as

$\alpha_{o\; 1} = {\frac{1}{{ølinks}\mspace{14mu}{per}\mspace{14mu}{source}\mspace{14mu}{document}\mspace{14mu}{issued}\mspace{14mu}{by}\mspace{14mu} o\; 1\mspace{14mu}{in}\mspace{14mu} 2004} = {\frac{1}{3} = 0.33}}$

For a particular document citation/document link dl2 issued by patentoffice o2 in 2004, a document linkage weight α_(o2) is calculated as

$\alpha_{o\; 2} = {\frac{1}{{ølinks}\mspace{14mu}{per}\mspace{14mu}{source}\mspace{14mu}{document}\mspace{14mu}{issued}\mspace{14mu}{by}\mspace{14mu} o\; 1\mspace{14mu}{in}\mspace{14mu} 2004} = {\frac{1}{4} = 0.25}}$

In the next step, ‘document family links’ are determined and weightedwith a document family linkage weight β.

According to embodiments of the invention, at first, all document linksare determined. Each document link connects a source document with adestination document. If at least one source document belonging to afirst document family links to a destination document, the destinationdocument belonging to another document family, a document family link isdetermined, whereby the first document family acts as source documentfamily and whereby the other document family acts as destinationdocument family of the determined document family link.

According to some embodiments of the invention, a document family linkis undirected. According to other embodiments, a document family link isa directed link pointing from the source document family to thedestination document family. According to some embodiments of theinvention, an undirected connection between document family A and B canbe modeled by a first document family link pointing from A to B and asecond document family link pointing from B to A.

After having determined ail document family links, a document familylinkage weight 3 is calculated for each determined document family link.Each document family linkage weight β is calculated for a particulardocument family link based on the document linkage weights on α₁, . . ., α_(m) of all document links dl₁, . . . , dl_(m) linking sourcedocuments of the source document family DF_(Source) to destinationdocuments of the destination document family DF_(Dest).

The existence of a single document link connecting one single sourcedocument of the first document family with one single destinationdocument of a second document family suffices to establish a documentfamily link. In this case, the calculated document family linkage weightβ solely depends on the document linkage weight α of said singledocument link.

According to a preferred embodiment, a document family linkage weightβ_(dl1, dl2) of a document family link connecting the source documentfamily df1 with destination document family df2 is derived bycalculating the maximum of all document linkage weights α₁, . . . ,α_(m) of all document links dl₁ . . . dl_(m) connecting documents ofdocument family df1 with documents of document family df2:β_(df1, df2)=MAXIMUM(α_(dl1), . . . α_(dlm)) For example, in case adocument family link is based on two document links dl1, dl2 connectingdocuments of a source document family df1 with documents of adestination family df2, and if α_(dl1)=0.25 and α_(dl1)=0.33, thenβ_(df1, df2)=MAXIMUM(α_(dl1), α_(dl2))=0.33.

According to further embodiments, the document family linkage weight iscalculated by using another arithmetic function such as the arithmeticmean, the median, the sum of the document linkage weights, the logarithmof the sum of the document linkage weights, the product of the documentlinkage weights, or any other function having been derived thereof.

For example, the document family linkage weight β could be calculated asβ_(df1, df2)=MEDIAN(α_(dl1), . . . α_(dlm)) or as SUM(α_(dl1), . . .α_(dlm)), or as ln(N+AGG(α_(dl1), . . . α_(dlm))), wherein N is a numberlarger than 0 and AGG is an aggregating function such as a sum, amedian, a mean and the like. According to preferred embodiments, N=1.

In the next step, an aggregate value γ_(DFDest) of all document familylinkage weights β of all document family links pointing from one ormultiple source document families d_(f1) . . . df_(n) to a destinationdocument family DF_(Dest.) is determined. The aggregate value can be,for example, calculated as the sum of all document family linkageweights of the document family links pointing to the destinationdocument family DF_(Dest):

γ_(DFDest.)=Σ_(n)(β_(df1), . . . β_(dfn)).

The aggregate value γ is indicative of the linkage relevance of thedocument family DF_(Dest): the higher the number of documents citingdocuments of document family DF_(Dest), and the higher the number ofdocument family links connecting various source document families toDF_(Dest), The higher the aggregate value γ.

According to further embodiments of the invention, the aggregate value γmay likewise be calculated based on another arithmetic function such asthe arithmetic mean, the median, the product, a maximum function or anyderivative thereof. Said other arithmetic function also operates on alldocument family linkage weights of all document family links pointing tothe destination document family DF_(Dest).

According to further embodiments, an additional weighting step isexecuted in order to weight document links from different fields independence on the relevance of the field for the interests of aparticular user. Each field f₁, . . . , f_(v) is assigned a user-definedrelevance value. Said user-defined relevance value is indicative of therelevance of a field for the user. According to embodiments, the fieldsof the one or more documents of a document family can also be assignedto the document family itself. This is, for example, the case withtechnology fields. Accordingly, each document family is assigned one ormore technology fields of its documents.

In a next step, each value β_(dfn) is weighted with the user-definedrelevance value assigned to the field f to which the source documentfamily has been assigned to. If the source document family has beenassigned to multiple fields, then the values β_(dfn) are weighted withe.g. the average, the median, the maximum or the minimum of theindividual field-specific user-defined relevance weights. The weightingstep can be accomplished, for example, by multiplying β_(dfn) with auser-defined relevance score for said field f. As a result, scoresγ_(DFDest) are returned as results, said results being normalizedaccording to the significance of different fields for the user. In caseeach document family is assigned to only one technology field, thefunction used could be:

γ_(DFDest.)=Σ_(n)(ε_(f1 df1)·β_(df1), . . . Σ_(fn dfn) ·βd _(fn))

The value ε_(fn dfn) is the relevance of the field fn assigned todocument family dfn for the interests of a particular user.

The aggregate value γ having been calculated for each destinationdocument family DF_(Dest) is returned as DFLS value of said documentfamily DF_(Dest).

Normalization

According to further embodiments of the invention, the aggregate value γof each destination document family can further be refined and itsaccuracy further be increased by normalizing said value in respect toe.g. a time period or field dependent reference value.

Calculating a Time Period Dependent Citation Statistic

According to some embodiments of the invention, the normalization stepis performed by calculating, for each time period z of a set of timeperiods z₁, . . . z_(k), an intermediate valueX1_(z=1)=ø(γ_(DFDest_1:z=1), . . . , γDF_(Dest_1:z=1)), . . . ,X1_(z=k)=ø(γ_(DFDest_1:z=k), . . . , γ_(DFDest_1:z=k)). The intermediatevalue X1_(2=y), for example, is an average of the aggregate value γ ofall document families whose status depends on a date lying within thetime period z=y, y being the time period for which X1 is calculated.

Said date can be, for example, the publication date of the earliestpublished document belonging to the document family DF_(Dest). Accordingto further embodiments of the invention, said data can also be thepriority date of a document family, whereby the document familyrepresent a patent family. According to further embodiments, said dateis the filing date of the earliest filed patent document belonging to adocument family, or is the earliest date of receiving patent protectionfor any of the patent documents belonging to the document/patent family.

According to some of said embodiments, the documents represent patentdocuments and the document families represent patent families.Accordingly, the time period z can be the year of first publication/thepriority year/the earliest year of tanning patent protection or thelike. Depending on the embodiment, said year can be a calendar year orcan be a time period of e.g. 12 months backwards starting from sheetdate. The “sheet date” is the date at which the method according toembodiments of the invention is executed or for which the relevancescores are calculated retrospectively.

According to further embodiments, shorter or longer periods of time thansaid 12 month may be used instead. If the method is executed on May 1,2010, the last k ‘years’ z₁-z_(k) would comprise the following timespans:

-   -   z₁: May 1 2009 to May 1 2010    -   z₂: May 1 2008 to May 1 2008    -   z₃: May 1 2007 to May 1 2007    -   Z_(k): May 1 (2010−k) to May 1 (2010−k+1)

The number k indicates the most distant year in the past stillconsidered for the calculation. For patent documents, k may range from20 to 100 years depending on the particular purpose of executing arelevance calculation. As patens usually expire after 20 years, theconsideration of years lying farther back in the past may be of use toevaluate historic developments of a patent portfolio along a greatertime span.

For example, for z=2004, the average ø_(z=2004) (γ_(DFDest_1:z=2004), .. . , γ_(DFDest_1:z=2004)) of all patent families DF_(Dest_1), . . . ,DF_(Dest_l) having e.g. their year of first publication z=2004, isdetermined, and an intermediate result X1_(z=2004) is calculated:

X1_(z=2004)=ø(γ_(DFDest_1,z=2004), . . . γ_(DFDest_l,z=2004))

The intermediate value X1 is indicative of the average aggregate value γper time period.

In order to allow the normalization of document family linkage scores,according to preferred embodiments of the invention, the averageaggregate value γ is calculated for each time period z₁-z_(k) bycalculating, for each time period, the average aggregate value and forall patent families DF_(Dest.z=x) having their date of firstpublication/priority date/first filing date within said time period.Accordingly, for all time periods z₁, . . . , z_(k), an intermediatevalue X1_(z=1), . . . , X1_(z=k) is calculated, thereby creating a timeperiod dependent citation statistics.

Calculating a Normalized Value δ for Each Patent Family DF_(Dest)

After having calculated for the set of time periods a time dependentcalculation statistic, said statistic is used to normalize theaggregated value γ of each document family in relation to all documentfamilies having the same period of first publication z (or, for otherembodiments: having the same priority period or the same period of firstfiling).

According to a preferred embodiment of the invention, for each documentfamily DF_(Dest.) a normalized aggregated value δDFDest is calculated.In case the period of first publication z of document family DF_(Dest.)is k, δDF_(Dest.) is calculated as follows.

$\delta_{{DFDest}.} = \frac{\gamma_{{DFDest}.}}{X\; 1_{z = k}}$

The intermediate value X1 is based on all document families having thesame period of first publication as the document family DF_(Dest)According to said embodiments, the calculated normalized aggregate valueδDF_(Dest.) of the document family DF_(Dest.) is calculated and returnedas DFLS value.

Calculating a Linkage Statistics Per Field:

A ‘field’ is a property of a document family, e.g. a technology field ofsaid document. According to further embodiments, a normalization stepbased on the field f of a document family DF_(Dest.) is executed. Saidnormalization step can be executed in addition to the time period basednormalization step. According to further embodiments, the field basednormalization may be executed without executing the time period specificnormalization by weighting the aggregate value γ by a weight factorbeing particular for the fields assigned to document family DF_(Dest).

-   a) In a first step, one or multiple fields f₁, . . . , f_(v) having    been assigned to the one or more document families are determined.

According to some embodiments of the invention, the documents are patentdocuments, the fields are technology fields and each document isassigned one or more IPC sub-class identifiers, each IPC sub-classidentifier representing a technology field. Each technology fieldassigned to a document of a document family is considered as technologyfield of the document family. A patent family may have been assigned toone or multiple IPC sub-classes. To give one example, the technologyfield f being based on the four digit IPC code ‘C07F’ relates tochemical substances comprising elements of the second group of theperiodic table of elements.

-   b) In a further step, an intermediate value X2TFf,z is calculated    for each of the fields f1, . . . , fv and for each of the time    periods z1, . . . zk.

Z indicates a lime period comprising a date such as the date of firstpublication, a priority date, the date of first filing a patent documentor the date of earliest granting of a patent for a patent document. Theexpressions “earliest” and “first” relates to other documents belongingto the same document family as said document.

The intermediate X2TF_(f,z) value is calculated as the average of allnormalized aggregate values δDF_(Dest.,f,z) of all document familiesDF_(Dest-.f,z) having been assigned to field f and having a statusdepending on the date lying within the same time period z;

For example, for z=12 (e.g. the year of first publications 2) andf=‘C07F’ the average ø_(z=12, f=C07F) (δ_(b:z=12, f=C07F)) of all patentfamilies having their year of first publication z=12 and having beenassigned to technology field f=‘C07F’ is determined. For example, if2233 document families are known to have assigned the year of firstpublication z=12 and the technology field f=C07F, the intermediateresult X2TF_(DFDest.:z=12, f=C07F) representing the average δ of allpatent families having a year of first publication z=12 and having beenassigned to technology field f=C07F and is calculated as:

X2TF _(DFDest:z=12,f=C07F).=ø_(z=12,f=C07F)(δ1_(b:z=12,f=C07F), . . .,δ2233_(b:z=12,f=C07F))

The symbol ø represents a mathematical function for calculating thearithmetic mean.

According to a preferred embodiment, X2TF is determined based on a timeperiod of two or three years or longer in case a set of documentfamilies of a particular year of first publication and of a particulartechnology field comprises less documents than a particular thresholdvalue, e.g. less than 200 items.

-   c) In a further step, an intermediate value X2 is calculated for    each document family DF_(Dest).

The intermediate value X2 is calculated as the average ø of allintermediate values X2TF_(f1,z), . . . , X2TF_(fm,z):

X2_(DFDest.)=ø(X2TF _(f1,z) , . . . ,X2TF _(fm,z))

Hereby, the intermediate values X2TF_(f1,z), . . . , X2TF_(fm,z) areintermediate values having been calculated for each field f₁, . . . ,f_(m), wherein each field f₁, . . . , f_(m) has been assigned to thedocument family DF_(Dest).

The field series f₁, . . . , f_(v) encompasses the totality of thespecified fields or the totality of fields assigned to any of the one ormore document families. The field series f₁, . . . , f_(m) encompassesthe totality of fields having been assigned to a particular documentfamily.

According to further embodiments, the value X2_(DFDest.) is calculatedby using another arithmetic function than the arithmetic mean, such asfor example the median, the minimum, the maximum, or any other functionhaving been derived thereof.

-   d) In a further step, for each document family DFDest, the final    DFLS value is calculated:

The DFLS value for a particular document family DF_(Dest.) is calculatedas the ratio of δ_(DFDest) to the intermediate value X2:

${DFLS}_{{DFDest}.} = \frac{\delta_{{DFDest}.}}{X\; 2}$

According to a further embodiment of the invention, the DFLS value maybe further refined to rise the accuracy of the DFLS by executing a DFLScorrection step on all document families having a date of firstpublication lying fewer than a maximum time threshold, e.g. 24 months,before the sheet date. According to one embodiment, the DFLS value forthose “particularly young” patent families is replaced by a predefinedor calculated score value. Said calculated score value could be, forexample, the average DFLS value having been calculated for patentfamilies of the same document owner, e.g. a company holding multiplepatent documents, said patent documents having a date of firstpublication during a time period lying more than said time threshold inthe past. By applying said correction, the relevance of youngerdocuments can be estimated more precisely. The “year of firstpublication” as used herein is the year when the first documentbelonging to a document family was published.

In other embodiments, said calculated score used for “particularlyyoung” patent families are derived from other properties of the documentfamily or are from derived scores such as for example the DFCS.

According to other embodiments, instead of the “year of firstpublication”, other document related data types can be used such as, forexample, the priority date of the patent family, the filing dale of theearliest filed patent document of a patent family, or the earliest dateof receiving patent protection for any of the patent documents belongingto the document family.

According to further embodiments, a modified method for calculating theDFLS score of a destination document family is provided.

According to embodiments making use of a first modified method forcalculating the DFLS score value, an X2B_(DFDest) value is calculatedinstead of the X2B_(DFDest) value. According to said embodiments,γ_(DFDest) values are used instead of δ_(DFDest) values for calculatingthe DFLS value. According to said embodiments, the DFLS value iscalculated by the following steps:

-   -   determining one or multiple fields f₁, . . . , f_(v) having been        assigned to the one or more document families,    -   calculating, for each field f₁, . . . , f_(v) and for each time        period z₁, . . . z_(k) an intermediate X2BTF_(f,z) value, the        intermediate X2BTF_(f,z) value being calculated as the average        of all aggregate values γ_(DFDest.f,z) of all document families        DF_(Dest-.f,z) having been assigned to field f and whose status        depends on the same kind of date, the date lying within the time        period z;    -   calculating, for each destination document family DF_(Dest), an        intermediate value X2B_(DFDest.), wherein        X2B_(DFDest.)=ø(X2BTF_(f1,z), . . . , X2BTF_(fm,z)), whereby the        intermediate values X2BTF_(f1,z), . . . , X2BTF_(fm,z) are        intermediate values having been calculated for each field f₁, .        . . , f_(m), the fields f₁, . . . , f_(m) each having been        assigned to the document family DF_(Dest),    -   calculating the DFLS value for each document family DF_(Dest) by        dividing γ_(DFDest) by X2B_(DFDest).

According to preferred embodiments, the ‘field’ is the technology fielda document family belongs to. The expression ‘the same kind of date’encompasses that the same type of event happened in time period z, saidtype of event being, for example, the date of first publication, thefiling date, the priority date of a document and the like.

According to embodiments making use of a second modified method forcalculating the DFLS score value, an additional weighting step isexecuted in order to weigh different fields in dependence on therelevance of the field for the interests of a particular user. Eachfield f₁, . . . , f_(v) is assigned a user-defined relevance value. Saiduser-defined relevance value is indicative of the relevance of a fieldfor the user. In a next step, each intermediate value X2TF_(f1,z), . . ., X2TF_(fv,z) is weighted with the user-defined relevance value assignedto the respective field f. The weighting step can be accomplished, forexample, by multiplying X2TF_(f,z) of the technical field f with auser-defined relevance score for said field f. As a result, intermediatevalues X3TF_(f1,z), . . . , X3TF_(fv,z) are returned as results, saidresults being normalized according to the significance of differentfields for the user. Finally, the returned X3TF_(f1,z), . . . ,X3TF_(fv,z) values are used instead of the intermediate X2TF_(f1,z), . .. , X2TF_(fv,z) values for calculating the X2 and DFLS values. Thecalculation of an X3TF score is an alternative to weighting the documentfamily linkage scores β with a user-defined relevance value ε assignedto each field as described beforehand. The calculation of an X3TF scoreis an alternative approach allowing taking into consideration therelevance of different fields for the interests of a user whencalculating the DFLS value for a document family.

4. Calculating for Each Document Family the DFCR Value:

the document family combined relevance score DFCR_(DFDest.) iscalculated for each document family by multiplying the document familycoverage score by the document family linkage score of document familyDFDest:

DFCR _(DFDest.) =DFCS _(DFDest.) ×DFLS _(DFDest.)

Embodiments of the invention wherein property-specific weights, e.g.weights being indicative of the significance of the country wherein adocument is valid, used for calculating the DFCS value are normalizedagainst an external data value such as the gross national product areparticularly advantageous in combination with applying a multiplicationof the DFCS value with the DFLS value for calculating the DFCR value.Normalizing the country specific weights w_(c) against an externalreference value is advantageous, as the calculated scores can becomprehended more easily: by calculating a normalized DFCS value, theDFCS value of a document family can be expressed in relation to anexternal reference value such as, for example, the gross nationalproduct of a country, and the numerical value of the DFCS score can bedecreased.

It has been observed that a multiplication of the two independentlyderived score values DFCS and DFLS is particularly advantageous andallows to increase the accuracy of calculating the relevance of adocument of a document family compared to methods which summarizedifferent relevance scores.

5. Grouping Document Families into One or More Portfolios, EachPortfolio Comprising One or More Document Families;

Depending on the embodiment of the invention, the grouping may be basedon predefined property values of the document data objects belonging toa document family or be based on the dynamic grouping of documentsfamilies executed by a clustering or machine-learning based algorithm.

According to embodiments of the invention, document families sharing oneor more property values or value ranges are grouped into the sameportfolio. Said property may be, for example,

-   -   the field of a document family,    -   the business field of a document family,    -   the company of a document family,    -   the document type of the document family,    -   the document kind code of a document family,    -   the organizational subunit of a company owning a document        family,    -   the branch of a company owning a document family,    -   the geographic region wherein a document family is valid or        where it originates from,    -   the status of a of a document family,    -   an IPC-class or sub-class,    -   a patent office.    -   a publisher or journal    -   the topic of the text of the document,    -   a time period,    -   a patent examiner,    -   a bibliographic feature such as the name of an author or an        inventor, or    -   a feature having been determined by a clustering algorithm        applied on the documents.

A person skilled in the art is able to adapt the set of properties orcriteria used to specify a portfolio as required by a particulardocument type and usage scenario. A portfolio, according to preferredembodiments of the invention, resembles any set of document familiesbased on which a user may be interested to derive an aggregate valuefrom it. For example, according to a preferred embodiment, documentfamilies are assigned to the same portfolio if they share the samedocument family owner, e.g. a company holding patent documents.According to other embodiments, portfolios may be defined by groups ofdocument families comprising documents which are, have been or willpotentially be valid within a particular geographic territory or whichare valid at a particular sheet date.

According to a preferred embodiment of the invention, the user isprovided with means to specify one or multiple properties according towhich the portfolios shall be defined. By providing a method forspecifying multiple properties based on which portfolios can be builtand an aggregating score value can be derived, the method provides meansfor deriving multi-dimensional score values aggregated based on amultitude of categories which may be of interest for a user, e.g. thecompany owning a document family or a department of the company havingcreated the invention a patent document family is based on.

6. Displaying, for Each Document Portfolio, an Aggregated View.

At least one aggregated score value is derived by an aggregatingfunction applied on one or more document family scores of all documentfamilies of the document portfolio. An aggregated score value isindicative of the aggregated relevance of the documents within a set ofdocument families, e.g. a portfolio. The document family scores used forcalculating an aggregate score function comprise the document familycombined relevance score DFCR, the document family linkage score DFLSand the document family coverage score DFCS. The aggregated viewdisplayed to the user e.g. in the form of a printout or a screencomprises and/or is derived from one or more aggregated score values.

According to a further embodiment of the invention, the user is providedwith means to specify which kind of aggregate score values shall becalculated and displayed. The aggregated score value of a portfolio maybe displayed e.g. in the form of a printout or on an electronic displaysuch as a screen. The aggregating function applied on said patent familyscore values may be, for example, a counting, summarization ormultiplication of score values or any derivative function thereof.

According to a preferred embodiment of the invention, the followingaggregate score values are calculated:

-   -   the portfolio size PSI, wherein the portfolio size of each        portfolio is calculated as the number of document families        within the portfolio having a DFCS value larger than 0;    -   the portfolio strength PST, wherein the portfolio strength of        each portfolio is calculated as the sum of the DFCR score values        of all document families within the portfolio. In case the        documents are patent documents, each patent family represents        one invention and the patent portfolio strength is the sum of        the DFCR score values of the inventions contained in the        portfolio.    -   the portfolio linkage score PLS, wherein the portfolio linkage        score is calculated for each portfolio as the average of the        DFLS values of all document families within the portfolio having        a document family coverage score value larger than 0;    -   the portfolio coverage score PCS, wherein the portfolio coverage        is calculated for each portfolio as the average of the document        family coverage scores of all document families within the        portfolio having a document family coverage score value larger        than 0;    -   the field share FSH. Ratio of the sum of the DFCR score values        of all document families of a portfolio and the sum of the DFCR        score values of a superset of document families, wherein the        document families of the portfolio and the document families of        the superset have assigned the same field for which the FSH is        calculated, e.g. if said document families have assigned a        particular technology field. The superset of document families        can be, for example, the totality of document families examined.

According to embodiments, the FSH value is calculated for a particularportfolio and a particular field by:

-   -   calculating a first sum as the sum of all DFCR values of all        document families having assigned said field and belonging to        said portfolio    -   calculating a second sum as the sum of all DFCR values of all        document families having assigned said field and belonging to a        superset of document families, said superset of document        families comprising said portfolio, and    -   calculating the ratio of the first and the second sum and using        said ratio as field share value FSH.

According to some embodiments, the field share is calculated as the sumof the DFCR scores of all the patent families assigned to a particularfield f, e.g. a technology field, and a particular portfolio, divided bythe sum of the DFCR scores of all patent families examined and havingbeen assigned to said field f.

According to some of said embodiments, said portfolio may be thetotality or a subset of all patent documents owned by a company. Tocalculate the FSH for a particular technological field and a particularportfolio of a company by said embodiment of the invention, it isrequired that each document family is assigned an identifier of thecompany owning the document family. The field share according to saidembodiments measures what share of the proprietary technology a companyis engaged in is owned by said particular company.

According to a preferred embodiment of the invention, the datastructures specifying a portfolio of document families provide theability to execute a multidimensional drill-down analysis of theaggregate relevance scores of all or a subset of document families of aportfolio. A multi-dimensional drill-down analysis of the aggregatescore in this context means that each portfolio and the documentfamilies contained therein may be further divided into several secondorder sub-sets of document families. Each sub-set comprises documentfamilies sharing a particular property, e.g. a particular year of firstpublication, a particular author, document owner, document type and soon. The patent portfolios are first-order sets of document families.Each portfolio may be further divided into second-, third-, fourth- orfifth order sub-sets. The division into sub-sets of document families isexecuted iteratively until a predefined or user-defined level ofanalysis granularity is reached. The aim of the multi-dimensionaldrill-down analysis is to provide the user with a fine-grainedcomparison and visual representation of the relevance of documentshaving been assigned to particular category of a particular hierarchicallevel.

According to a further embodiment of the invention, the user is providedvia a graphical user interface with means to select, during thedrill-down analysis, a document-family sub-set of an arbitrary level ofthe hierarchy of document family sub-sets. As a result of saidselection, the documents or document families of the selected sub-set ofdocument families is displayed to the user, wherein the displayeddocuments or document families are ranked according to any of the DFCR,the DFLS or the DFCS values or derivatives thereof.

According to a further embodiment of the invention, themulti-dimensional drill-down analysis is executed to determine theaggregate score value ‘field share’. Thereby, the documents representpatents, the document families are patent families and a DFCR score iscalculated for every document family DF_(Dest.) as described previously.FIG. 8 shows the aggregated field share of four companies. In case alldocument families available are used in this analysis, the drill-downanalysis would comprise two dimensions: one dimension represents thecompany for which the field share is calculated, the second dimensionrepresents the aggregate score value of all document families of aparticular company, in this case the aggregate PFCI score values of allpatent families of a company. The analysis may further drill-down into athird dimension by further grouping the field share values of aparticular company according to the year of first publication of eachdocument family considered (see the bars of the field share in FIG. 8for the years 1998-2003 wherein one bar represents a particular sheetdate). According to further embodiments, a fourth dimension ofdrill-down analysis may be applied, e.g. by further dividing the fieldshare of each particular company reached m each particular yearaccording to the various R&D departments run by each company.

The type of criteria chosen for the drill-down analysis of data as wellas the type of aggregated relevance score (PSI, PST, FSH, PLS, PCS)calculated on each portfolio, sub-set and sub-sub set of documentfamilies depends on the particular use case (the document type, theproperties assigned to each document, the topic a user executing thedrill-down analysis considers as ‘relevant’ and the degree of analysisgranularity the user considers appropriate).

According to a preferred embodiment of the invention, the drill-downanalysis of document families is implemented based on OLAP cubes. AnOLAP (Online analytical processing) cube is a data structure arrangingdata into cubes. The cube structure provides the possibility to executea drill-down analysis of the data contained in the cube. Drilling down adata space is an analytical technique whereby the user navigates amonglevels of data ranging from the most summarized (up) to the mostdetailed (down). By representing the set of document families assignedto a particular portfolio in the form of an OLAP cube, an aggregatescore value can be derived on multiple levels of document familysubsets. The aggregate score may be calculated based on one or multipleaggregate functions executed on the DFCS, DFLS or DFCR value(s) of alldocument families assigned to a particular portfolio or document familysub-set on any level of the drill-down hierarchy. The term‘portfolio-coverage’ or ‘portfolio-size’ does not imply that saidaggregate function is applied solely on the document families within aparticular portfolio, the first-order set of document families. Rather,it can be applied to any sub-set of document families within saidportfolio in case a drill-down analysis of data is requested by theuser.

According to a preferred embodiment of the invention, the portfolios aswell as their sub-sets of document families are defined based onparticular properties of the document families.

According to further embodiments of the invention, the portfolios or anyof the sub-sets of document families of the portfolios are determined byexecuting a clustering or a classification algorithm on the documentfamilies. A classification algorithm is an algorithm according to whichdocument families are assigned to predefined categories, e.g. to a listof companies or countries of interest. A clustering algorithm is analgorithm being able to group together document families being stronglyrelated to each other while separating document families beingsignificantly different from each other in respect to one or severalproperties of interest wherein the final groups, also called ‘clusters’,do not necessarily have to be specified in advance. Various clusteringand classification methods are known to a person skilled in the art andhave to be chosen depending on the type of documents and on theinterests of the user. The applied clustering or classification methodmay result in overlapping or non-overlapping groups of documentfamilies. A method allowing different document family clusters orclasses to overlap may be appropriate to separate document familiesaccording to features which are not mutually exclusive: a patent familymay be assigned to multiple different technology fields, but it cannothave multiple different years of first publication. In order to groupdocument families into clusters or classes according to the latter kindof property, non-overlapping clustering or classification approaches maybe more appropriate.

According to a further embodiment of the invention, the aggregated scorevalue(s) calculated by any of the described aggregate score functions ofvarious portfolios or subclasses are displayed graphically in the formof a graphical element displayed e.g. on a computer screen or aprintout. Alternatively, said calculated score values are not displayeddirectly but are used to specify graphical elements being indicative ofa particular score value or score value range. Said graphical elementcan be a chart, e.g. a barchart, line-chart, pie-chart, block-chart, a2D or 3D chart or the like. The graphical element may also be a symbol,a geographic, organizational or other map.

According to embodiments, said graphical elements are characterized byone or more layout properties, said layout properties being indicativeof the aggregated score value or value range. Depending on theembodiment, the layout property can be a color, a shape, a hatching, orthe like. For example, a set of colors (a color schema) can be used toencode an aggregated score value range.

According to embodiments of the invention, the aggregated view comprisesthe numeric value of the aggregated score value or one or more graphicalelements, said graphical elements being characterized by one or morelayout properties, said layout properties being indicative of theaggregated score value or value range.

According to embodiments of the invention, the aggregated view comprisesa chart, the chart being indicative of one or more aggregated scorevalues.

According to a further embodiment of the invention, the graphicalelement, e.g. a symbol or a chart, is displayed on top of a geographicmap in case the aggregate score value represented by the graphicalelement has been calculated for a particular geographic region. Byplacing the graphical element on top of the geographic region theaggregate score value has been calculated for, the user gets a quick andintuitive impression of the aggregated score value of all documentfamilies having been assigned to said geographic region.

According to embodiments, the aggregated score is indicative of theeconomic relevance of all patent documents valid within a particulargeographic region.

According to a further embodiment of the invention, the aggregate scorevalues and/or graphical elements like symbols, charts, color-codedmap-regions or other color-encoded elements representing such scorevalues are presented to remote users via a network, e.g. by displayingsaid graphical elements on a web-page being accessible via the Internetor intranet of a company.

All said display options based on graphical elements or numbers beingindicative of an aggregate relevance score such as a FSH, PST, PSI, PCSor the like are subsumed as the provision of an “aggregated view”.

According to a further embodiment, the position of a document family orfor a symbol or figure representing an aggregate score value of a set ofdocument families is determined by the following steps:

-   -   Determine the addresses of the person or company owning a        document, e.g. a patent document,    -   determine, e.g. by calling an external web service,        geo-coordinates of the addresses derived in the first step,    -   Display the aggregated score value or a symbol representing this        value on a geographic map.

According to a further embodiment, the weighted document family linksdetermined during the calculation of the DFLS can be used to determinethe net information flow between geographic regions in a time dependentmanner. As document families can be assigned to countries directly orcan be assigned to persons or companies owning the documents which canbe mapped to geo-coordinates via their addresses, it is possible todetermine if e.g. in a particular year 1999 as many document familylinks pointed from India to the USA as in the opposite direction, and ifthe sum of all document family linkage weights from one country to theother differ. In case the number and weight of document family linkspointing from India to the USA exceeded for several years those pointingfrom the USA to India, this indicates an information flow from the USAto India in said period. This information is an additional beneficialaspect of the method for quantifying the relevance of documents.

In a further aspect, the invention relates to a corresponding computersystem comprising said storage medium, a processor for executing theinstructions on said storage medium and comprising graphical outputmeans for displaying the aggregated view provided by said method.

In a further aspect, the present invention relates to a computerimplemented method for quantifying and ranking the relevance ofdocuments, the documents being represented by document data objects, themethod comprising:

-   -   assigning documents to one or multiple document families, each        document family comprising one or multiple documents;    -   calculating, for each document family, a document family        coverage score DFCS, the document family coverage score being        indicative of the validity of the document family in a category,        whereby the validity is calculated from one or more properties        of each document belonging to said document family;    -   calculating, for each document family, a document family linkage        score DFLS, said document family linkage score being calculated        by        -   finding one or more document links, each document link            connecting a source document to a destination document, each            destination document belonging to said document family, each            source document belonging to another document family,        -   finding one or more document family links, whereby each            document family link connects a source document family with            said document family, said document family acting as            destination document family, wherein the existence of each            document family link is derived from the one or more found            document links and wherein the DFLS is derived from the            existence and weight of the one or more found document            family links;    -   calculating, for each document family, a document family        combined relevance score DFCR by multiplying the document family        coverage score DFCS and the document family linkage score DFLS        having been calculated for each document family;    -   ranking all documents or document families according to the        calculated DFCS value, the DFLS value, the DFCR value, or any        derivative thereof.

Different embodiments of said method exist according to which the DFCS,DFCR and DFLS values are calculated as described for differentembodiments of the method for quantifying and aggregating the relevanceof documents.

In a further aspect, the invention relates to a computer implementedmethod for calculating a document family linkage score value fordocument families, the document families being represented by dataobjects, the method comprising the steps:

-   -   assigning documents to one or multiple document families, each        document family comprising one or multiple documents;    -   finding one or more document links, each document link        connecting a source document to a destination document,    -   determining, for each document link connecting source document        d1 with destination document d2, a document linkage weight        α_(d1,d2);    -   determining all document family links, whereby each document        family link connects a source document family with a destination        document family, wherein the existence and weight of each        document family link is derived from one or more document links        connecting source documents of the source document family to        destination documents belonging to the destination document        family;    -   determining for each document family link, a document family        linkage weight β, the document family linkage weight β being        derived from the weights of the document links linking documents        of the source document family DF_(Source) to documents of the        destination document family DF_(Dest),    -   calculating for each destination document family DF_(Dest.) an        aggregate value γ as a derivative of the linkage weights        β_(DFSource_j DFDest) truest of all document family links        pointing from one or multiple source document families to        destination document family DF_(Dest.)    -   returning the calculated aggregate value γ as document linkage        score value of the destination document family.

Different embodiments of said method exist according to which thedocument family linkage score value is calculated as described fordifferent embodiments of the method for quantifying and aggregating therelevance of documents.

Embodiments of the invention solely making use of a linkage-based scorevalue are advantages in case the calculation of a document familycoverage score is computationally expensive. In addition, solelylinkage-based scores allow the comparison of document families ofdifferent types, including also those for which no document familycoverage score can be calculated.

In a further aspect, the present invention relates to a computerreadable storage medium comprising instructions which, when executed bya processor, cause the processor to execute a method for quantifying andaggregating the relevance of documents according to any of the methodsdescribed above.

In a further aspect, the present invention relates to a computerreadable storage medium comprising instructions which, when executed bya processor, cause the processor to execute a method for quantifying andranking the relevance of documents according to any of the methodsdescribed above.

According to further embodiments of the invention, the computer readablestorage medium composes instructions which, when executed by theprocessor, cause the processor to calculate a document family linkagescore DFLS according to any of the methods described above.

In a further aspect, the invention relates to a computer systemcomprising a processor and a computer readable storage medium comprisinginstructions for executing the method for quantifying and aggregatingthe relevance of documents, the method for quantifying and ranking therelevance of documents or the method for calculating the DFLS value ofdocument families according to any of the above embodiments. Saidcomputer system further comprises a graphical output means such as anelectronic display, a printer, or a network connection to a remotedisplay means.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following, embodiments of the invention are described by way ofexample, only making reference to the drawings in which:

FIG. 1 is a flowchart providing an overview on the method forquantifying the relevance of documents, also referred to as ‘PortfolioBenchmarking’,

FIG. 2 is a flowchart illustrating the step of defining documentfamilies, e.g. patent families, in greater detail,

FIG. 3 is a flowchart illustrating the step of calculating the DFCS of adocument family in greater detail,

FIGS. 4a-c represent a flowchart spreading over multiple pages whichillustrates the step of calculating the DFLS of a document family ingreater detail,

FIG. 5 illustrates the determination of document family linkage weights(step 404) and the value γ (step 405) graphically,

FIG. 6 is a block diagram of a computer system according to oneembodiment of the invention,

FIG. 7 is a flow chart illustrating possible use case scenarios ofembodiments of the invention other than portfolio benchmarking,

FIG. 8 is a bar chart illustrating the field share of four companies,

FIG. 9 is a line chart illustrating the average PFCI score values of allinventions within the portfolios of four companies, and

FIG. 10 is a table displayed to a user, the table comprising multipleaggregate score values of the patent portfolios of four companies.

FIG. 1 provides an overview on the method for quantifying the relevanceof documents. The method for quantifying the relevance of documents isalso referred to as ‘Portfolio Benchmarking’. In case the documents arepatents, the method according to embodiments of the invention providesan improved method for quantifying the significance, e.g. the economicrelevance, of patent documents.

After the portfolio benchmarking method has been started in step 100,document families are defined in step 101 by assigning multipledocuments to document families having one or multiple properties incommon, e.g. referring to the same invention. On the data object level,this step implies connecting document data objects of the same documentfamily to each other e.g. by adapting the values of document data objectattributes or by creating entries in association tables of data bases.The criterion according to which documents are assigned to documentfamilies depends on the type of documents. In case the documents arepatent documents, the patent documents referring to the same thirdpatent document as priority document or referring to each other aspriority documents are grouped into one document family, here calledpatent family. All patent documents of a patent family represent thesame invention. In step 104, document families whose documents share areparticular property are grouped into portfolios; For example, if alldocuments are patent documents and all document families are patentfamilies, document families may be grouped to portfolios if they sharethe same owner, here referred to as patent holder, usually a company.The owner may be a person or a company or any other institution and is,according to a preferred embodiment, derived from properties of thedocument data objects assigned to the document family. In case thedocuments are patents, each document may comprise information on theapplicant, usually a company, holding the patent. In step 102, thevalidity of each document is examined. This step comprises testingwhether the meta-information of the document data object comprisessufficient and consistent data, e.g. on the legal status of a documentin a country or other pieces of data which may be of relevance insucceeding processing steps. According to a preferred embodiment of theinvention, patent documents being not patent documents and patentapplications in the strict meaning of the word, e g. utility patents andutility patent applications, are filtered out in this step. In addition,patent documents issued from patent offices providing only insufficientdata on the legal status may be filtered out here.

In step 103, the DFCS value is calculated for each document family (DF)which will be explained in greater detail by FIG. 3. In step 105, theDFLS value is calculated for each document family DF which will beexplained in greater detail by FIGS. 4a -4 c.

In step 106, for each document family b the DFCR score value iscalculated as the product of the DFCS_(v) and foe DFLS_(b) value of saidfamily.

In step 113, one or multiple aggregate relevance scores, e.g. theportfolio size PSI, the portfolio strength PST, the field share FSH, theportfolio linkage score PLS or the portfolio coverage score PCS, arecalculated on foe DFCS, DFLS and DFCR score values of all documentfamilies within a portfolio. A portfolio may comprise the totality ofdocument families available and managing to pass the validity check instep 102 or any document family sub-set thereof. According to preferredembodiments of the invention, each portfolio comprises all documentfamilies being owned by the same person or company.

According to embodiments of the invention, one or multiple of thefollowing aggregate score values are calculated:

-   -   The portfolio size PSI is calculated in step 107 and represents        the total number of document families of a portfolio having a        DFCS value greater than 0.    -   The portfolio strength PST is calculated in step 108 as the sum        of the DFCR values of all document families of a portfolio.    -   The field share FSH is calculated in step 109 as the ratio of        the sum of the DFCR score values of all document families of a        portfolio and the sum of the DFCR score values of a superset of        document families, whereby only document families having        assigned a particular field of interest are considered According        to said embodiment, the field share FSH measures what share of        the proprietary technology of the industry is owned by a certain        company. It can be calculated as the share of the Patent        Portfolio Strength of a company in the total Patent Portfolio        Strength of all companies in the industry. Depending on the        embodiment, the FSH value can also be calculated as the share of        the Patent Portfolio Strength of a company in a particular        technology field in relation to the total Patent Portfolio        Strength of all patent families in that technology field. It can        also be calculated as a share of a PST value of an arbitrary        sub-portfolio derived by grouping patent families according to        e.g. some criteria A and B compared to a total PST value of a        portfolio derived by grouping patent families according to e.g.        criteria A.    -   The portfolio linkage score PLS is calculated in step 110 as the        average of the DFLS value of all document families of the        portfolio with a DFCS value greater than 0. The portfolio        linkage score is indicative of the relevance of a portfolio.    -   The portfolio coverage score PCS is calculated in step 111 as        the average of all DFCS values of all document families of the        portfolio with a DFCS value greater than 0.

Finally, the end of the benchmarking method is reached in step 112.

FIG. 2 illustrates the definition of document families as indicated inFIG. 1. step 101 in greater detail. The embodiment of the inventiondepicted in FIG. 2 describes the grouping of documents being patents topatent families.

After starting the definition of patent families in step 200, a list ofdocuments, according to the described embodiment, patent documents,describing the same invention is created in step 201. Two documentsdescribe the same invention and are assigned to one patent family, if

-   -   a) both documents share at least one priority document, which        means that it is checked whether the ID and the date of priority        of the priority document referred to by both documents is        identical, or    -   b) one document cites the other document as priority document.

In step 202, the document families are filtered and only those patentfamilies are kept which comprise at least one patent document whichmeets a list of quality criteria. Said at least one patent documentmust:

-   -   a) represent a patent document in the narrow sense of the word,        including patents and patent applications but excluding utility        patents and utility patent applications    -   b) have been published not earlier than Jan. 1, 1970.

According to a preferred embodiment of the invention, all documents ofthe resulting filtered patent families remain in a the databaseirrespective of whether the documents individually meet the qualitycriteria.

The definition of document families, here described for the case ofpatent families, ends with step 203.

FIG. 3 illustrates the calculation of the document family coverage scoreDFCS for each document family b as indicated in FIG. 1 by step 103 ingreater detail. The calculation for the document family b starts withstep 300 and ends with step 304 and is executed for all documentfamilies within a portfolio. The embodiment of the invention depicted inFIG. 3 calculates the DFCS values for patent documents. In case thedocuments whose relevance is to be quantified are not patent documents,the method will after minor adaptations e.g. for the determination ofthe validity status of a document within a country be applicable aswell.

In step 301, the validity of all documents DOC of the document family b,here a patent family, is determined for all countries c for all sheetdates of interest according to the following rules:

In case the first date of filing DOC in a country c happened earlierthan sheet date and if sheet date is earlier than the date of expirationof the patent in country c. then a document DOC is considered as validin country c. As a result, document family b comprising DOC is alsoconsidered as valid in country c.

A list of sheet dates of interest may, for example, be December 31. ofthe years 1998-2003.

Each country c is assigned a weighting factor w_(c), for each documentDOC of document family b which is calculated as follows:

-   -   w_(c) is 0, if the sheet date is later or identical to the date        of expiration of the patent which was granted in country c based        on DOC.    -   w_(c) is 0, if the sheet date is earlier than the first date of        filing DOC.    -   w_(c) is 0.7, if the first date of filing DOC is earlier than or        equal to sheet date and sheet date is earlier than the date of        expiration of the property right based on DOC in country c and        sheet date is earlier than the day the patent is granted.    -   w_(c) is 1, if grant date of DOC is earlier than or equal to        sheet date and sheet date is earlier than the expiration date of        the patent granted on DOC in country c.

In the next step 303, the weighting factors wc of each country c anddocument DOC are further weighted according to the impact of thiscountry. According to a preferred embodiment of the invention, thisweighting is done by multiplying the weighting factor obtained for aparticular country c in the previous step, which is either 0, 0.7 or 1,by a country specific weight indicating the significance of the country,e.g. its gross national income GNI. The obtained value is divided by theGNI of a reference country, e g. the GNI of the USA, to obtain arelative, country specific weight of the impact of the invention in aparticular country c in relation to a patent filed or granted in theUSA:

wp _(c)=[w _(c) *GNI _(c)]/GNI _(USA)

The GNI figures represent external data and are derived according topreferred embodiments of the invention on an annual basis from the WorldBank. According to further embodiments of the invention, said globaleconomic key figures are replaced by figures which better represent theeconomic impact of a country in respect to a particular business ortechnology field, e.g. sales figures of the pharmaceutical industries orof automobile manufacturers.

The final DFCS value for patent family b is calculated by summing up forall countries c the weighted factors wp_(c) obtained on the documentsDOC of the document family:

DFCS _(b)=Σ_(c) wp _(c).

To further improve the accuracy of the relevance quantification, furtherembodiments of the invention consider PCT and EP patent applicationsaccording to the following rules:

Pending EP-applications are treated as patent applications in all EPCstates until either the patent is granted or the application isabandoned, depending on which of the two options takes place earlier.

WO-applications are considered as equivalent to patent applications inall PCT states within the first 40 month after the first date of filing.

If a national patent application exists in addition to a PCT or an EPapplication, the respective country is not considered twice.

FIGS. 4a-c illustrate the calculation of the document family linkagescore DFLS for all document families as indicated in FIG. 1 by step 105in greater detail. The calculation starts in step 400 and ends in step412. The embodiment of the invention depicted in FIGS. 4a-c calculatesthe DFLS values for patent documents.

In step 402, a statistics is created for every patent office about whichsufficient data is available. In this step, the average number of patentdocuments cited as prior art documents by a patent office o for a patentapplication per year y is determined. The value obtained is referred toas CS_(o,y) wherein o is indicative of the patent office and y of theyear.

In step 403, all document links connecting documents contained in thetotality of documents to be examined are determined and to everydocument link a document linkage weight α is assigned. A document linkis a link connecting a source document with a destination document.According to a preferred embodiment of the invention, each prior artcitation of a patent document issued for each patent document by apatent office is considered as a document link. A database table iscreated comprising all document links in association with itscorresponding source document, destination document and document linkageweight α. The document linkage weight α depends on the citation qualityof the patent office issuing each link. The higher the number ofcitations issued by a patent office per patent document, the lower therelevance and quality of the citation in respect to a particular patentdocument. The value α is therefore determined for each document linkbased on the patent office issuing the link as α=1/CS_(o,y). Thedetermination and weighting of document links is depicted graphically ingreater detail in FIG. 5.

In step 404, all weighted document family links within the total set ofexamined document families are determined. A database table is createdcomprising all document family links. Each document family link entry ofthat table also comprises its corresponding source document familyDF_(Source), its destination document family DF_(Dest.) and its documentfamily linkage weight β. A document family acts as source documentfamily being connected with a destination document family via a documentfamily link if the source document family comprises at least onedocument linking to a document belonging to the destination documentfamily. According to a preferred embodiment, the document family linkageweight β is calculated as the MAXIMUM value of all document linkagevalues α connecting documents of the source document family withdocuments of the destination document family.

β_(DFSource,DFDest.)=MAXIMUM(α₁,α₂, . . . α_(n)).

In step 405, the value γ is calculated for every document familyDF_(Dest). The value γ is calculated as the sum of the document familylinkage weights of all document family links connecting a sourcedocument family i with document family DF_(Dest).

γD _(FDest.)=Σ_(i)β_(DFSource_i,DFDest.)

The calculation of γ_(DFDest.) is depicted graphically in greater detailin FIG. 5.

In step 406, a citation statistic for all years of first publication zis created. This task comprises the calculation of the average γ of alldocument families having the same year of first publication z. Everydocument family is characterized by a year of first publication z whichrepresents, for patent documents, the first year wherein any of thedocuments belonging to a document family was published. An intermediatevalue X1 is calculated for each year of first publication z and all γ ofall document families having a year of first publication z:

X1_(r)=ø(γ_(DFDest.)).

According to the depicted embodiment of the invention, the documentlinks are based on citations. The document family links are derived fromthe document links and are therefore also based on citations. Citationbased relevance scores of documents have a strong bias towards olderdocuments as older documents had a greater chance of becoming cited thanrecently published documents. Therefore, according to some embodiments,the intermediate value X1 is corrected for the last two years before thesheet date. To calculate X1 for the last two years, the average ofDF_(Dest) of the third year ahead of the sheet date is used for thecalculation. A ‘year’ in this context is a time period of 12 monthdetermined in relation to the current date, not a calendar year.

In step 407, the value δ is calculated for every document familyDF_(Dest). The value δ_(DFDest.) is calculated as the ration of theγ_(DFDest.) value and the average of all t patent families having thesame year of first publication z:

δ_(DFDest.)=γ_(DFDest.)/ø(γ_(DF1),γ_(DF2), . . . ,γ_(DFt))

In step 408, a citation statistics is calculated for all technologyfields f considered. The average δ of all document families having ayear of first publication z per technology field f is calculated. Thetechnology fields are defined by the first four digits of the IPCclassification (IPC subclasses). Every document family having beenassigned to an IPC subclass (irrespective of the assigning patentoffice) is considered.

An intermediate value X2TF_(f,z) is calculated for each year of firstpublication z considered, e.g. the last 50 years from the current date,and for all technology fields f of interest. X2TF_(f,z) is calculated asthe average S of all document families having a year of firstpublication z and having been assigned to the technology field f (adocument family can have assigned one or multiple technology fields).

X2TF _(f,z)=ø(δ_(f,z))

In cases less than 200 document families exist for a particulartechnology field, the calculation of X2TF_(f,z) is not based on anaverage value derived from the year of first publication z but ratherfrom an average value based on multiple years.

In step 409, the document family linkage score DFLS is calculated forevery document family DF_(Dest) The step comprises two sub-steps. Atfirst, the one or multiple technology fields f to which DF_(Dest.) hasbeen assigned to is determined. The average value from all X2TF_(f,z)values corresponding to technology fields having been assigned todocument family DF_(Dest) and having the same year of first priority iscalculated and referred to as intermediate value X2.

X2_(DFDest.)=ø(X2TF _(f1_DFDest,z_DFDest.) ,X2TF _(f2_DFDest,z_DFDest.), . . . ,X2TF _(fn_DFDest.,z_DFDest.))

The X2TF_(f1_DFDest., z_DFDest.). X2TF_(f2_DFDest., z_DFDest.) values donot have to be calculated de novo in step 409, as said values have beencalculated already for each technology field f and each year of firstpublication z in step 408. It is only required to retrieve theappropriate X2TF value for the technology fields and the year of firstpublication of document family DF_(Dest.) whose DFLS is to becalculated.

In the next sub-step, the DFLS value of the document family DF_(Dest.)is calculated as the ratio of δ_(DFDest.) and X2_(DFDest.)

DFLS _(DFDest.)=δ_(DFDest.) /X2_(DFDest.)

In decision 410 it is determined whether the benchmarking method isexecuted for a company or not. According to an embodiment of theinvention, the user is provided with means, e.g. a GUI, to selectbetween the two options ‘YES: portfolio benchmarking for a company’ and‘No’. In case the option ‘Yes’ is selected, a further step 411 isexecuted adapting the DFLS value calculated in step 409 for patentdocuments being younger than 24 month. Patent documents being youngerthan 24 month are assigned a predefined or calculated other value. Saidother value is, for example, the average DFLS value calculated fordocument families held by the company for which the portfoliobenchmarking is executing and having and whose age is between e.g. 24 to48 month, the age of a patent document being calculated based on thefiling date. In case the second option ‘No’ is selected, the calculationof the DFLS value of document family DF_(Dest) is terminated in step412. The ‘No’ option may be preferentially selected if the portfoliobenchmarking is executed for instances other than companies or forcompanies which do not own patent documents older than 24 month’.

The determination and weighting of document family links is depictedgraphically in greater detail in FIG. 5.

FIG. 5 illustrates the steps 404, the determination and weighting ofdocument links, and step 405, the determination and weighting ofdocument family links, graphically. Step 404 is represented by the leftblock of the figure comprising a document families DF_(Dest.) 500 andDF_(Source) 501, 500 comprising the documents d4, d5 and d6, 501comprising the documents d7, d8 and d3. A first document link 506connects the source document d8 with the destination document d5.According to some embodiments of the invention, such a link may bederived by a patent office issuing a citation of patent document d5 asprior art document when examining patent document d8. A second documentlink 505 connects source document d3 to destination document d6. Linkageweight α_(d6,d5) is assigned to document link 506 and α_(d3,d6) isassigned to document link 505. In case document links 505 and 506 havebeen issued from different patent offices having different citationquality, the document links 505 and 506 have assigned two differentdocument linkage weights α_(d3,d6) and α_(d8,d5).

According to further embodiments of the invention, the document linkageweight α is not calculated based on the citation quality of the patentoffice but rather on the citation quality of a patent examiner workingat a patent office. Again, the higher the average number of prior artcitations issued by a patent examiner per patent document, the lower isthe quality and relevance of a single citation issued by said examiner,α is calculated analogously to the patent office based weighting, butinstead of patent office specific scores patent examiner specific scoresare used for the weighting.

Analogously, according to further embodiments of the invention, documentlinks are weighted based on the average number of prior art patentdocument citations assigned to a patent document in a particulartechnology field. The higher said average, the lower is considered thequality of each single citation and the lower the weight of each singledocument link connecting documents of a particular technology field.

The weight β1 of a single document family link, indicated in FIG. 5 bythe dashed ellipse surrounding the document links 505 and 506, iscalculated as the maximum document linkage weight α of ail documentlinks connecting a source document in source document family 501 to adestination document in destination document family 500:β1=MAXIMUM(α_(d8,d5), α_(d3,d6)).

The right box of FIG. 5 representing step 405 illustrates thecalculation of γ_(DFDest) by summing up all document family linkageweights β1, β2 directing from a source document family DF1 _(Source)501, DF2 _(Source) 503 to destination document family DF_(Dest) 500. Thedocument family linkage weight β1 corresponds to document family link507 while the document family linkage weight β2 corresponds to documentfamily link 504.

γ_(DFDest)=Σ(β1,β2)

FIG. 6 is a block diagram of a computer system 600 comprising aprocessor 601 and a computer readable storage medium 602.

While the machine-readable medium 602 is shown in an exemplaryembodiment to be a single medium, the term “machine-readable medium”should be taken to include a single medium or multiple media (e.g., acentralized or distributed database, and/or associated caches andservers) that store the one or more sets of instructions. The term“machine-readable medium” shall also be taken to include any medium thatis capable of storing or encoding a set of instructions 603 forexecution by the machine and that cause the machine to perform any oneor more of the methods of the present invention. The term“machine-readable medium” shall accordingly be taken to include, but notbe limited to, solid-state memories, optical and magnetic media, and thelike. The set of instructions may also reside, completely or at leastpartially, within the main memory and/or within the processor duringtheir execution by the computer system 600, the main memory 606 and theprocessor 601 also constituting machine-readable media. The calculatedaggregate score values and/or their visual representations may bedisplayed on a display 607 being part of the computer system, e.g. ascreen, or be transmitted to the remote display 604 over a network 605via the network interface 608 utilizing any one of a number ofwell-known transfer protocols (e.g., HTTP).

The computer-implemented method described herein requires physicalmanipulations of physical quantities. Usually, though not necessarily,these quantities take the form of electrical or magnetic signals capableof being stored, transferred, combined, compared, and otherwisemanipulated. It has proven convenient at times, principally for reasonsof common usage, to refer to these signals as bits, values, elements,symbols, characters, terms, numbers, or the like. It should be borne inmind, however, that all of these and similar terms are to be associatedwith the appropriate physical quantities and are merely convenientlabels applied to these quantities. Unless specifically stated otherwiseas apparent from the discussion herein, it is appreciated thatthroughout the description, discussions utilizing terms such as“processing” or “computing” or “calculating” or “determining” or thelike, refer to the action and processes of a computer system, or similarelectronic computing device, that manipulates and transforms datarepresented as physical (electronic) quantities within the computersystem's registers and memories into other data similarly represented asphysical quantities within the computer system memories or registers orother such information storage, transmission or display devices.

The computer-readable instructions may be stored in a computer readablestorage medium 602, such as, but not limited to, any type of diskincluding floppy disks, optical disks, CD-ROMs, and magnetic-opticaldisks, read-only memories (ROMs), random access memories (RAMs) such asdynamic RAM (DRAM), EPROMs, EEPROMs, magnetic or optical cards, or anytype of media suitable for storing electronic instructions, and eachcoupled to a computer system bus.

The present invention is not described with reference to any particularprogramming language. It will be appreciated that a variety ofprogramming languages may be used to implement the teachings of theinvention as described herein.

FIG. 7 illustrates that the score values DFOLS, DFCS and DFCR shown inbox 702 can be used in method 703 for portfolio benchmarking asdescribed previously. In addition or alternatively, the document familyscore values can be used to rank all document families or the documentscontained therein and to present in step 706 the user only the mostrelevant documents or document families e.g. on a screen of a computer.The document family scores may also be used in method 704 to execute adrill-down analysis, thereby determining aggregate score values ofvarious sub-sets of document families, e.g. of all document familieshaving a year of first priority 1997, being owned by company A andbelonging to a particular technology field f. The aggregate score valuesobtained from the portfolio benchmarking or from themultidimensional-drill-down analysis can be displayed in dense form as achart or color-encoded geographic map on a screen.

FIG. 8 depicts a bar chart being indicative of the field share of fourcompanies A-D in the years 1998 to 2003 at a particular sheet date, e.g.December 31. The field share may be calculated for all technology fieldsavailable or for patent families belonging to a limited, preselected setof technology fields only. The pre-selection of technology fields beforecomparing the field share of various companies is advantageous, as thedegree according to which companies are engaged in a particulartechnology field may vary and a large company owning a multitude ofpatens does not necessarily comprise a large document portfolio in everytechnology field the company is engaged in. The field shares of alldocument families belonging to all companies A-D and belonging to aparticular technology field altogether yield a total share of 100%.

FIG. 9 depicts a line chart being indicative of the average combinedrelevance of all inventions of four companies E-H in the years 1998 to2003 at a particular sheet date, e.g. December 31. Each invention isrepresented by a patent family. By considering multiple years, thedevelopment of the average combined relevance of a patent portfolio canbe monitored.

FIG. 10 depicts a table 1000 comprising multiple aggregate score valuescalculated for the patent portfolios of four companies l-L. The tablecomprises several columns for the field share 1002, the portfoliostrength 1003, the portfolio size 1004, the average DFCR score value ofall document families of a company 1005, the average DFLS value of alldocument families of a company 1007, and the average age of theinventions in the patent portfolio 1008. Column 1007 represents the sizeof the markets covered by patents of a company compared to the size of areference market size, e g. the US market size. The average combinedrelevance is calculated as the average of ail DFCR scores of all patentfamilies displayed in column 1005 is larger than the product of theaverage DFLS value of a company depicted in column 1006 and the averageDFCS value of a company depicted in column 1007. These two numbersdiffer because companies systematically seek broader coverage for morerelevant patents.

Although the invention herein has been described with reference toparticular embodiments, it is to be understood that these embodimentsare merely illustrative of the principles and applications of thepresent invention. It is therefore to be understood that numerousmodifications may be made to the illustrative embodiments and that otherarrangements may be devised without departing from the spirit and scopeof the present invention as defined by the appended claims.

Abbreviations

-   -   GNI Gross National Income    -   OLAP online analytical processing    -   DFCS document family coverage score    -   DFLS document family linkage score    -   DFCR document family combined relevance score    -   FSH field share    -   PST portfolio strength    -   PSI portfolio size    -   PLS portfolio linkage score    -   PCS portfolio coverage score    -   DOCDB EPO patent information resource    -   INPADOC-PRS INternational PAtent DOCumentation

LIST OF REFERENCE NUMERALS

-   -   100-112 steps    -   200-203 steps    -   300-304 steps    -   305 GNI figures of World Bank    -   400-412 steps    -   500 document family DF_(Dest.)    -   501 document family DF1 _(Source)    -   503 document family DF2 _(Source)    -   504 document family link    -   505 document link from d3 to d6    -   506 document link from d8 to d5    -   507 document family link    -   600 computer system    -   601 processor    -   602 storage medium    -   603 instructions    -   604 remote display means    -   605 network    -   606 main memory    -   607 display means    -   608 network interface    -   702 list of document family scores    -   703-704 steps    -   800 bar chart: field share    -   900 line chart: avg. DFCR    -   1000 table comprising mult. aggreg. scores    -   1001 company column    -   1002 FSH column    -   1003 PST column    -   1004 PSI column    -   1005 avg. DFCR column    -   1006 avg. DFLS column    -   1007 avg. DFCR column    -   1008 avg. age column

1. A computer implemented method comprising: assigning documents to oneor more document families, each document family comprising one or moredocuments, wherein each document is selected from a group consisting ofa patent document and a patent application document; calculating, foreach document family, a document family coverage score DFCS, thedocument family coverage score being indicative of the validity of thedocument family in a category, whereby the validity is calculated fromone or more first properties of each document belonging to said documentfamily; calculating, for each document family, a document family linkagescore DFLS, said document family linkage score being calculated byfinding one or more document links, each document link connecting asource document to a destination document, each destination documentbelonging to said document family, each source document belonging toanother document family; finding one or more document family links,whereby each document family link connects a source document family withsaid document family, said document family acting as destinationdocument family, whereby the existence of each document family link isderived from the one or more found document links and wherein the DFLSis derived from the existence and weight of the one or more founddocument family links; and calculating, for each document family, adocument family combined relevance score DFCR by multiplying thedocument family coverage score DFCS and the document family linkagescore DFLS having been calculated for each document family.
 2. Thecomputer implemented method according to claim 2, further comprising:grouping document families into one or more portfolios, each portfoliocomprising one or more document families; and densely displaying, foreach document portfolio, an aggregated view in which a plurality of datavalues are displayed in a summarized form on a graphical user interfacewith the summarized form providing a visualization of relationshipsbetween all documents in the document portfolio, the aggregated viewcomprising or being derived from one or more aggregated score values,the one or more aggregated score values being calculated by applying anaggregating function on the DFCR, the DFLS, or the DFCS value of the oneor more document families of said portfolio.
 3. The computer implementedmethod according to claim 2, wherein the categories are geographicterritories and the first properties are countries.
 4. The computerimplemented method according to claim 3, wherein the DFCS of eachdocument family is calculated by summing up weights assigned to eachdocument of the document family, each weight w_(c) being indicative of asignificance of the country c.
 5. The computer implemented methodaccording to claim 2, wherein each weight w_(c) is multiplied with avalue being indicative of a significance of the country c and the DFCSof each document family b at a sheet date is calculated as DFCS(document family b)=Σ([w_(c)*GNI_(c)]/GNI_(REF)), wherein w_(c) is acountry specific weight of country c, country c having been assigned tothe document; wherein Σ indicates the sum over all documents of adocument family and for all countries c considered; wherein GNI_(c) is aparameter being indicative of a significance of country c; and whereinGNI_(REF) is a reference parameter being indicative of a significance ofa reference country REF.
 6. The computer implemented method according toclaim 2, wherein each value being indicative of a significance of acountry can be replaced by a user-specific value, and wherein areference parameter GNI_(REF) can be selected or specified by the uservia the graphical user interface, wherein the weight w_(c) is indicativeof a legal status of the document, wherein said legal status is selectedfrom the group consisting of a valid patent status, an expired statusand a pending legal status, wherein a patent document has valid patentstatus in a country if the granting date of the patent <=sheet date<date of expiration of the patent, wherein the document has pendinglegal status in a country if: the date of filing the document is <=sheetdate, and if sheet date is <date of expiration of the document; and ifthe granting date >sheet date wherein the document has expired status ina country if sheet date >=expiration date or wherein sheet date <date offiling of the document; and wherein the weight w_(c) for pending statusis a score value indicating the probability that a patent will begranted for the document.
 7. The computer implemented method accordingto claim 2, where the document links are weighted and are indicative ofcitations of prior art patent documents, the method further comprisingthe steps: calculating, for each document link, a document linkageweight α, the document linkage weight being a quality measure of thedocument link; calculating, for each document family link, a documentfamily linkage weight β, the document family linkage weight β being aderivative of the document linkage weights α of all document linksconnecting source documents of one source document family withdestination documents of one destination document family; calculating,for each destination document family, an aggregate value γ as aderivative of all document family linkage weights β of all documentfamily links connecting a source document family with the destinationdocument family; and returning the calculated aggregate value γ as DFLSvalue.
 8. The computer implemented method according to claim 7, whereinthe document linkage weight α is selected from the group comprising: apatent office specific quality value, said patent office specificquality value being indicative of the quality of the citations issued bythe patent office, wherein the document link quality value is inverselyproportional to the average number of cited documents of said patentoffice; a patent examiner specific quality value, said patent examinerspecific quality value being indicative of the quality of the citationsissued by the patent examiner, wherein the document link quality valueis inversely proportional to the average number of cited documents ofsaid patent examiner; a citing authority specific quality value, saidciting authority specific quality value being indicative of theauthority having cited a particular document, said authority being inparticular an inventor, an examiner or a 3rd party; a citation categoryof the destination document; a property of the destination document,said property being indicative of the relevance of said destinationdocument to the user; a property of the source document, said propertybeing indicative of the relevance of said source document to the user; aquality value being derived from the technology field of the sourcedocument, said quality value being inversely proportional to the averagenumber of documents cited by a document having assigned said technologyfield; and a quality value being derived from the technology field ofthe source document and the technology field of the destination documentsaid quality value being derived from a predefined or dynamicallycalculated similarity score, the similarity score being indicative ofthe similarity of the technology field of the source document and thetechnology field of the destination document.
 9. The computerimplemented method according to claim 7, wherein each document familylinkage weight β_(DFSource), D_(FDest.) is equal to the maximum documentlinkage weight MAX(α_(ALL)); the average document linkage weightAVG(α_(ALL)); the median document linkage weight MEDIAN(α_(ALL)); thesummed-up document linkage weight SUM(α_(ALL)); or the logarithmicdocument linkage weight being calculated as ln(N+α_(AGG)) orlog(N+α_(AGG)), wherein N is a natural integer >0, wherein α_(ALL)represents all document linkage weights of all document links connectingsource documents belonging to the document family DF_(Source) withdestination documents belonging to the destination document familyDF_(Dest) and wherein α_(AGG) represents a data value having beencalculated by aggregating all of said document linkage weights α_(ALL).10. The computer implemented method according to claim 7, wherein thedocuments are patent documents, wherein the document links arecitations, and wherein the document linkage weight α_(d1, d2) isdetermined for each document link by: determining the average number ofprior art citations CS_(o, y) issued by a patent office o per patentdocument and per time period z; calculating for each document link thedocument linkage weight α_(d1, d2) as α_(d1, d2)=1/CS_(o, z), wherein oindicates the patent office issuing the citation, the citationcorresponding to the document link to be weighted, and wherein zindicates the time period z in which the citation was issued by thepatent office.
 11. The computer implemented method according to claim 7,wherein the step of calculating the aggregate value γ_(DFDest) comprisesin addition the execution of a normalization step, the normalizationstep comprising: calculating, for each time period z of a set of timeperiods z_(i), . . . z_(k) an intermediate value X1_(z), theintermediate value X1_(z) being the arithmetic mean of the aggregatevalue γ of all document families whose status depends on a date lyingwithin the time period z, wherein the date is selected from the groupcomprising the publication date of the earliest published documentbelonging to the document family; the priority date of the patentfamily; the filing date of the earliest filed patent document belongingto the document family; and the earliest date of receiving patentprotection for any of the patent documents belonging to the documentfamily; determining a normalized aggregated value δ_(DFDest) of eachdocument family DF_(Dest) whose status depends on a date lying withinthe time period z, wherein δ_(DFDest)=γ_(DFDest)/X1_(z); returningδ_(DFDest) as DFLS value of document family DF_(Dest).
 12. The computerimplemented method according to claim 11, wherein the normalization isexecuted in addition in respect to at least one field f, the methodfurther comprising the steps: determining one or more fields fl, . . .fV having been assigned to the one or more document families;calculating, for each field fl, . . . , fV and for each time period zl,. . . zk an intermediate X2TF_(f,z) value, the intermediate X2TF_(f,z)value being calculated as the average of all normalized aggregate valuesδ_(DFDest,f,z) of all document families DF_(Dest,f,z) having beenassigned to field f and whose status depends on the same kind of date,the date lying within the time period z; calculating, for eachdestination document family DFDest, an intermediate value X2DF_(Dest),wherein X2DF_(Dest)=ø(X2TF_(fl,z), . . . , X2TF_(fm,z)), whereby theintermediate values X2TF_(fl,z), . . . , X2TF_(fm,z) are intermediatevalues having been calculated for each field fl, . . . , fm, the fieldsfl, . . . , fm each having been assigned to the document familyDF_(Dest); calculating the DFLS value for each document family DF_(Dest)by dividing δ_(DFDest) by X2_(DFDest).
 13. The computer implementedmethod according to claim 7, further comprising the steps: determiningone or more fields f₁, . . . , f_(v) having been assigned to the one ormore document families; calculating, for each field f₁, . . . , f_(v)and for each time period zl, . . . zk an intermediate X2BTF_(f,z) value,the intermediate X2BTF_(f,z) value being calculated as the average ofall aggregate values γ_(DFDest,f,z) of all document familiesDF_(Dest,f,z) having assigned the field f and whose status depends onthe same kind of date, the date lying within the time period z;calculating, for each destination document family DF_(FDest), anintermediate value X2BDF_(Dest), wherein X2BDF_(Dest)=ø(X2BTF_(fl,z), .. . , X2BTF_(fm,z)), whereby the intermediate values X2BTF_(fl,z), . . ., X2BTF_(fm,z) are intermediate values having been calculated for eachfield fl, . . . , fm, the fields fl, . . . , fm each having beenassigned to the document family DF_(Dest); calculating the DFLS valuefor each document family DF_(Dest) by dividing γ_(DFDest) byX2BDF_(Dest.).
 14. The computer implemented method according to claim 2,wherein the aggregated score value is selected from a group comprising:a field share value FSH, the field share value being calculated for saidportfolio for one field f, whereby a field is a property of a documentfamily and wherein each document family has assigned at least one field,the field share value FSH being calculated for said field f by:calculating a first sum as the sum of all DFCR values of all documentfamilies having assigned said field f and belonging to said portfolio;calculating a second sum as the sum of all DFCR values of all documentfamilies having assigned said field f and belonging to a superset ofdocument families, said superset of document families comprising saidportfolio; calculating the ratio of the first and the second sum andusing said ratio as field share value FSH; a portfolio size PSI, whereinthe portfolio size of each portfolio is calculated as the number ofdocument families within the portfolio having a DFCS value larger than0; a portfolio strength PST, wherein the portfolio strength of eachportfolio is calculated as the sum of the DFCR score values of alldocument families within the portfolio; a portfolio linkage score PLS,wherein the portfolio linkage score is calculated for each portfolio asthe average of the DFLS values of all document families within theportfolio having a document family coverage score value larger than 0; aportfolio coverage score PCS, wherein the portfolio coverage iscalculated for each portfolio as the average of the document familycoverage scores of all document families within the portfolio having adocument family coverage score value larger than
 0. 15. The computerimplemented method according to claim 2, wherein document familiessharing one or more first or second property values or value ranges aregrouped into the same portfolio, said first or second properties beingselected from the group comprising: a technology field; a businessfield; a company owning the document; a document type; a document kindcode; a organizational subunit of a company owning or creating thedocument; a branch of a company owning the document; a geographic regionof origin or validity of the document; a status of the document; apatent office; a publisher or journal; the topic of the text of thedocument; a patent examiner; a time period; an IPC-class or sub-class; abibliographic feature such as the name of an author or an inventor; anda feature having been determined by a clustering algorithm applied onthe document data objects, wherein via each of said first or secondproperties one or more document portfolios can be specified upon whichthe aggregating function can be applied.
 16. The computer implementedmethod according to claim 15, wherein the document families within eachof the one or more document portfolios are iteratively grouped intosecond-, third-, fourth- or nth-order document-family sub-sets, therebybuilding a hierarchy of document-family sub-sets; wherein the first orsecond property shared by the document families within eachdocument-family sub-set is different in each level of the hierarchy ofdocument-family sub-sets; and wherein an aggregated score value iscalculated for any document family subset of the document family sub-sethierarchy.
 17. The computer implemented method according to claim 16,wherein the step of displaying, for each document portfolio, anaggregated score value further comprises the steps: providing the userwith means to select a document-family sub-set at an arbitrary level ofthe hierarchy of document family sub-sets; and displaying, via thegraphical user interface, the document families or documents containedwithin the selected sub-set of document families, the displayeddocuments or document families being ranked according to any of thedocument family score values DFCR, DFLS, DFCS or derivatives thereof.18. A computer implemented method comprising: assigning documents to oneor more document families, each document family comprising one or moredocuments; calculating, for each document family, a document familycoverage score DFCS, the document family coverage score being indicativeof the validity of the document family in a category, wherein thevalidity is calculated from one or more first properties of eachdocument belonging to said document family; calculating, for eachdocument family, a document family linkage score DFLS, said documentfamily linkage score being calculated by finding one or more documentlinks, each document link connecting a source document to a destinationdocument, each destination document belonging to said document family,each source document belonging to another document family; finding oneor more document family links, wherein each document family linkconnects a source document family with said document family, saiddocument family acting as destination document family, wherein theexistence of each document family link is derived from the one or morefound document links and wherein the DFLS is derived from the existenceand weight of the one or more found document family links; calculating,for each document family, a document family combined relevance scoreDFCR by multiplying the document family coverage score DFCS and thedocument family linkage score DFLS having been calculated for eachdocument family; grouping document families into one or more portfolioseach comprising one or more document families; densely displaying, foreach document portfolio, an aggregated view m which a plurality of datavalues are displayed in a summarized form on a graphical user interfacewith the summarized form providing a visualization of relationshipsbetween all documents in the document portfolio, the aggregated viewcomprising or being derived from one or more aggregated score values,the one or more aggregated score values being calculated by applying anaggregating function on the DFCR, the DFLS, or the DFCS value of the oneor more document families of said portfolio, wherein the documents arepatent documents or patent applications, and wherein the calculation ofthe relevance score for each document family further comprisescalculating the DFLS value of a first document family whose statusdepends on a date lying within a time period zx, the time period zxbeing younger than a threshold time value, by calculating an averageDFLS value of all DFLS values having been calculated for one or moresecond document families of the same portfolio.
 19. A non-transitorycomputer readable storage medium containing instructions that whenexecuted by a processor cause the processor to perform operationscomprising: assigning documents to one or more document families, eachdocument family comprising one or more documents, wherein each documentis selected from a group consisting of a patent document and a patentapplication document; calculating, for each document family, a documentfamily coverage score DFCS, the document family coverage score beingindicative of the validity of the document family in a category, wherebythe validity is calculated from one or more first properties of eachdocument belonging to said document family; calculating, for eachdocument family, a document family linkage score DFLS, said documentfamily linkage score being calculated by finding one or more documentlinks, each document link connecting a source document to a destinationdocument, each destination document belonging to said document family,each source document belonging to another document family; finding oneor more document family links, whereby each document family linkconnects a source document family with said document family, saiddocument family acting as destination document family, whereby theexistence of each document family link is derived from the one or morefound document links and wherein the DFLS is derived from the existenceand weight of the one or more found document family links; andcalculating, for each document family, a document family combinedrelevance score DFCR by multiplying the document family coverage scoreDFCS and the document family linkage score DFLS having been calculatedfor each document family.
 20. The computer implemented method accordingto claim 1, where the document links are weighted and are indicative ofcitations of prior art patent documents.